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{
"cells": [
{
"cell_type": "markdown",
"id": "a10cd722",
"metadata": {},
"source": [
"# Preprocessing"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "59819858",
"metadata": {},
"outputs": [],
"source": [
"import matplotlib\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"import sklearn\n",
"import time\n",
"import openpyxl as xls\n",
"\n",
"from sklearn.preprocessing import MinMaxScaler\n",
"from sklearn.preprocessing import label_binarize\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.naive_bayes import GaussianNB\n",
"from sklearn.neighbors import KNeighborsClassifier\n",
"from sklearn.metrics import classification_report\n",
"from sklearn.metrics import confusion_matrix\n",
"from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n",
"from sklearn.metrics import roc_curve,auc\n",
"from sklearn.metrics import roc_auc_score"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "bb54cf3f",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>jenis_kelamin</th>\n",
" <th>umur</th>\n",
" <th>tinggi_badan_meter</th>\n",
" <th>berat_badan_kilogram</th>\n",
" <th>histori_keluarga_kelebihan_BB</th>\n",
" <th>konsumsi_tinggi_kalori</th>\n",
" <th>konsumsi_sayuran</th>\n",
" <th>makan_berat</th>\n",
" <th>ngemil</th>\n",
" <th>merokok</th>\n",
" <th>konsumsi_air_liter</th>\n",
" <th>pemantauan_kalori</th>\n",
" <th>aktifitas_fisik</th>\n",
" <th>penggunaan_perangkat_teknologi</th>\n",
" <th>konsumsi_alkohol</th>\n",
" <th>transporasi_biasa_digunakan</th>\n",
" <th>kelas_obesitas</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.62</td>\n",
" <td>64</td>\n",
" <td>Ya</td>\n",
" <td>Tidak</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.52</td>\n",
" <td>56</td>\n",
" <td>Ya</td>\n",
" <td>Tidak</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Ya</td>\n",
" <td>Lebih 2 liter</td>\n",
" <td>Ya</td>\n",
" <td>4-5 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Laki-laki</td>\n",
" <td>29</td>\n",
" <td>1.62</td>\n",
" <td>53</td>\n",
" <td>Tidak</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Perempuan</td>\n",
" <td>23</td>\n",
" <td>1.50</td>\n",
" <td>55</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Transportasi umum</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Laki-laki</td>\n",
" <td>22</td>\n",
" <td>1.64</td>\n",
" <td>53</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>4-5 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>443</th>\n",
" <td>Perempuan</td>\n",
" <td>37</td>\n",
" <td>1.55</td>\n",
" <td>76</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>444</th>\n",
" <td>Perempuan</td>\n",
" <td>39</td>\n",
" <td>1.56</td>\n",
" <td>76</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>445</th>\n",
" <td>Perempuan</td>\n",
" <td>37</td>\n",
" <td>1.50</td>\n",
" <td>75</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>446</th>\n",
" <td>Perempuan</td>\n",
" <td>41</td>\n",
" <td>1.54</td>\n",
" <td>77</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>Lebih 2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>447</th>\n",
" <td>Perempuan</td>\n",
" <td>43</td>\n",
" <td>1.59</td>\n",
" <td>77</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>Lebih 2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>448 rows × 17 columns</p>\n",
"</div>"
],
"text/plain": [
" jenis_kelamin umur tinggi_badan_meter berat_badan_kilogram \\\n",
"0 Perempuan 21 1.62 64 \n",
"1 Perempuan 21 1.52 56 \n",
"2 Laki-laki 29 1.62 53 \n",
"3 Perempuan 23 1.50 55 \n",
"4 Laki-laki 22 1.64 53 \n",
".. ... ... ... ... \n",
"443 Perempuan 37 1.55 76 \n",
"444 Perempuan 39 1.56 76 \n",
"445 Perempuan 37 1.50 75 \n",
"446 Perempuan 41 1.54 77 \n",
"447 Perempuan 43 1.59 77 \n",
"\n",
" histori_keluarga_kelebihan_BB konsumsi_tinggi_kalori konsumsi_sayuran \\\n",
"0 Ya Tidak Kadang-kadang \n",
"1 Ya Tidak Selalu \n",
"2 Tidak Ya Kadang-kadang \n",
"3 Ya Ya Selalu \n",
"4 Tidak Tidak Kadang-kadang \n",
".. ... ... ... \n",
"443 Ya Ya Kadang-kadang \n",
"444 Ya Ya Kadang-kadang \n",
"445 Ya Ya Kadang-kadang \n",
"446 Ya Ya Kadang-kadang \n",
"447 Ya Ya Kadang-kadang \n",
"\n",
" makan_berat ngemil merokok konsumsi_air_liter pemantauan_kalori \\\n",
"0 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"1 3x Kadang-kadang Ya Lebih 2 liter Ya \n",
"2 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"3 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"4 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
".. ... ... ... ... ... \n",
"443 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"444 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"445 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"446 3x Kadang-kadang Tidak Lebih 2 liter Tidak \n",
"447 3x Kadang-kadang Tidak Lebih 2 liter Tidak \n",
"\n",
" aktifitas_fisik penggunaan_perangkat_teknologi konsumsi_alkohol \\\n",
"0 Tidak pernah 0-2 jam Tidak pernah \n",
"1 4-5 hari 0-2 jam Kadang-kadang \n",
"2 Tidak pernah 0-2 jam Kadang-kadang \n",
"3 1-2 hari 0-2 jam Kadang-kadang \n",
"4 4-5 hari 0-2 jam Kadang-kadang \n",
".. ... ... ... \n",
"443 1-2 hari 0-2 jam Kadang-kadang \n",
"444 Tidak pernah 0-2 jam Kadang-kadang \n",
"445 Tidak pernah 0-2 jam Kadang-kadang \n",
"446 Tidak pernah 0-2 jam Kadang-kadang \n",
"447 Tidak pernah 0-2 jam Kadang-kadang \n",
"\n",
" transporasi_biasa_digunakan kelas_obesitas \n",
"0 Sepeda motor kelebihan_berat_badan \n",
"1 Sepeda motor kelebihan_berat_badan \n",
"2 Jalan kaki normal \n",
"3 Transportasi umum kelebihan_berat_badan \n",
"4 Sepeda motor normal \n",
".. ... ... \n",
"443 Jalan kaki obesitas_II \n",
"444 Jalan kaki obesitas_II \n",
"445 Jalan kaki obesitas_II \n",
"446 Jalan kaki obesitas_II \n",
"447 Jalan kaki obesitas_II \n",
"\n",
"[448 rows x 17 columns]"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data = pd.read_csv('dataset/data_obesitas.csv')\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "42396def",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 448 entries, 0 to 447\n",
"Data columns (total 17 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 jenis_kelamin 448 non-null object \n",
" 1 umur 448 non-null int64 \n",
" 2 tinggi_badan_meter 448 non-null float64\n",
" 3 berat_badan_kilogram 448 non-null int64 \n",
" 4 histori_keluarga_kelebihan_BB 448 non-null object \n",
" 5 konsumsi_tinggi_kalori 448 non-null object \n",
" 6 konsumsi_sayuran 448 non-null object \n",
" 7 makan_berat 448 non-null object \n",
" 8 ngemil 448 non-null object \n",
" 9 merokok 448 non-null object \n",
" 10 konsumsi_air_liter 448 non-null object \n",
" 11 pemantauan_kalori 448 non-null object \n",
" 12 aktifitas_fisik 448 non-null object \n",
" 13 penggunaan_perangkat_teknologi 448 non-null object \n",
" 14 konsumsi_alkohol 448 non-null object \n",
" 15 transporasi_biasa_digunakan 448 non-null object \n",
" 16 kelas_obesitas 448 non-null object \n",
"dtypes: float64(1), int64(2), object(14)\n",
"memory usage: 59.6+ KB\n"
]
}
],
"source": [
"data.info()"
]
},
{
"cell_type": "markdown",
"id": "f8d9da3c",
"metadata": {},
"source": [
"### distribusi kelas "
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "c90d7b2b",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>kelas_obesitas</th>\n",
" <th>jumlah</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>berat_badan_kurang</td>\n",
" <td>85</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>normal</td>\n",
" <td>141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>71</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>obesitas_I</td>\n",
" <td>85</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>obesitas_II</td>\n",
" <td>66</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" kelas_obesitas jumlah\n",
"2 berat_badan_kurang 85\n",
"0 normal 141\n",
"3 kelebihan_berat_badan 71\n",
"1 obesitas_I 85\n",
"4 obesitas_II 66"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"kelas_obesitas = data['kelas_obesitas'].value_counts().rename_axis('kelas_obesitas').reset_index(name='jumlah')\n",
"urutan_obesitas = ['berat_badan_kurang',\n",
" 'normal',\n",
" 'kelebihan_berat_badan',\n",
" 'obesitas_I',\n",
" 'obesitas_II']\n",
"kelas_obesitas['kelas_obesitas'] = pd.Categorical(kelas_obesitas['kelas_obesitas'], categories=urutan_obesitas, ordered=True)\n",
"kelas_obesitas = kelas_obesitas.sort_values(by='kelas_obesitas')\n",
"kelas_obesitas"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "626df08e",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 500x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(5, 5))\n",
"colors = sns.color_palette('pastel')\n",
"\n",
"plt.pie(kelas_obesitas['jumlah'], labels=kelas_obesitas['kelas_obesitas'], autopct='%1.1f%%', colors=colors)\n",
"\n",
"plt.title('Perbandingan Persentase Kelas Obesitas')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "aa77f287",
"metadata": {},
"source": [
"### cek outlier"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "a6bde44e",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1500x1000 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize = (15,10))\n",
"sns.boxplot(data = data, orient='h')\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "1e29416d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 448 entries, 0 to 447\n",
"Data columns (total 17 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 jenis_kelamin 448 non-null object \n",
" 1 umur 448 non-null int64 \n",
" 2 tinggi_badan_meter 448 non-null float64\n",
" 3 berat_badan_kilogram 448 non-null int64 \n",
" 4 histori_keluarga_kelebihan_BB 448 non-null object \n",
" 5 konsumsi_tinggi_kalori 448 non-null object \n",
" 6 konsumsi_sayuran 448 non-null object \n",
" 7 makan_berat 448 non-null object \n",
" 8 ngemil 448 non-null object \n",
" 9 merokok 448 non-null object \n",
" 10 konsumsi_air_liter 448 non-null object \n",
" 11 pemantauan_kalori 448 non-null object \n",
" 12 aktifitas_fisik 448 non-null object \n",
" 13 penggunaan_perangkat_teknologi 448 non-null object \n",
" 14 konsumsi_alkohol 448 non-null object \n",
" 15 transporasi_biasa_digunakan 448 non-null object \n",
" 16 kelas_obesitas 448 non-null object \n",
"dtypes: float64(1), int64(2), object(14)\n",
"memory usage: 59.6+ KB\n"
]
}
],
"source": [
"data.info()"
]
},
{
"cell_type": "markdown",
"id": "20c810b7",
"metadata": {},
"source": [
"### transformasi"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "d412e9f6",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>jenis_kelamin</th>\n",
" <th>umur</th>\n",
" <th>tinggi_badan_meter</th>\n",
" <th>berat_badan_kilogram</th>\n",
" <th>histori_keluarga_kelebihan_BB</th>\n",
" <th>konsumsi_tinggi_kalori</th>\n",
" <th>konsumsi_sayuran</th>\n",
" <th>makan_berat</th>\n",
" <th>ngemil</th>\n",
" <th>merokok</th>\n",
" <th>konsumsi_air_liter</th>\n",
" <th>pemantauan_kalori</th>\n",
" <th>aktifitas_fisik</th>\n",
" <th>penggunaan_perangkat_teknologi</th>\n",
" <th>konsumsi_alkohol</th>\n",
" <th>transporasi_biasa_digunakan</th>\n",
" <th>kelas_obesitas</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0</td>\n",
" <td>21</td>\n",
" <td>1.62</td>\n",
" <td>64</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0</td>\n",
" <td>21</td>\n",
" <td>1.52</td>\n",
" <td>56</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" <td>1.62</td>\n",
" <td>53</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0</td>\n",
" <td>23</td>\n",
" <td>1.50</td>\n",
" <td>55</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" <td>1.64</td>\n",
" <td>53</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>443</th>\n",
" <td>0</td>\n",
" <td>37</td>\n",
" <td>1.55</td>\n",
" <td>76</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>444</th>\n",
" <td>0</td>\n",
" <td>39</td>\n",
" <td>1.56</td>\n",
" <td>76</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>445</th>\n",
" <td>0</td>\n",
" <td>37</td>\n",
" <td>1.50</td>\n",
" <td>75</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>446</th>\n",
" <td>0</td>\n",
" <td>41</td>\n",
" <td>1.54</td>\n",
" <td>77</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>447</th>\n",
" <td>0</td>\n",
" <td>43</td>\n",
" <td>1.59</td>\n",
" <td>77</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>448 rows × 17 columns</p>\n",
"</div>"
],
"text/plain": [
" jenis_kelamin umur tinggi_badan_meter berat_badan_kilogram \\\n",
"0 0 21 1.62 64 \n",
"1 0 21 1.52 56 \n",
"2 1 29 1.62 53 \n",
"3 0 23 1.50 55 \n",
"4 1 22 1.64 53 \n",
".. ... ... ... ... \n",
"443 0 37 1.55 76 \n",
"444 0 39 1.56 76 \n",
"445 0 37 1.50 75 \n",
"446 0 41 1.54 77 \n",
"447 0 43 1.59 77 \n",
"\n",
" histori_keluarga_kelebihan_BB konsumsi_tinggi_kalori konsumsi_sayuran \\\n",
"0 1 0 1 \n",
"1 1 0 2 \n",
"2 0 1 1 \n",
"3 1 1 2 \n",
"4 0 0 1 \n",
".. ... ... ... \n",
"443 1 1 1 \n",
"444 1 1 1 \n",
"445 1 1 1 \n",
"446 1 1 1 \n",
"447 1 1 1 \n",
"\n",
" makan_berat ngemil merokok konsumsi_air_liter pemantauan_kalori \\\n",
"0 2 1 0 2 0 \n",
"1 2 1 1 3 1 \n",
"2 2 1 0 2 0 \n",
"3 2 1 0 2 0 \n",
"4 2 1 0 2 0 \n",
".. ... ... ... ... ... \n",
"443 2 1 0 2 0 \n",
"444 2 1 0 2 0 \n",
"445 2 1 0 2 0 \n",
"446 2 1 0 3 0 \n",
"447 2 1 0 3 0 \n",
"\n",
" aktifitas_fisik penggunaan_perangkat_teknologi konsumsi_alkohol \\\n",
"0 0 1 0 \n",
"1 3 1 1 \n",
"2 0 1 1 \n",
"3 1 1 1 \n",
"4 3 1 1 \n",
".. ... ... ... \n",
"443 1 1 1 \n",
"444 0 1 1 \n",
"445 0 1 1 \n",
"446 0 1 1 \n",
"447 0 1 1 \n",
"\n",
" transporasi_biasa_digunakan kelas_obesitas \n",
"0 1 kelebihan_berat_badan \n",
"1 1 kelebihan_berat_badan \n",
"2 4 normal \n",
"3 3 kelebihan_berat_badan \n",
"4 1 normal \n",
".. ... ... \n",
"443 4 obesitas_II \n",
"444 4 obesitas_II \n",
"445 4 obesitas_II \n",
"446 4 obesitas_II \n",
"447 4 obesitas_II \n",
"\n",
"[448 rows x 17 columns]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data['jenis_kelamin'] = data['jenis_kelamin'].replace('Laki-laki', 1)\n",
"data['jenis_kelamin'] = data['jenis_kelamin'].replace('Perempuan', 0)\n",
"\n",
"data['histori_keluarga_kelebihan_BB'] = data['histori_keluarga_kelebihan_BB'].replace('Ya', 1)\n",
"data['histori_keluarga_kelebihan_BB'] = data['histori_keluarga_kelebihan_BB'].replace('Tidak', 0)\n",
"\n",
"data['konsumsi_tinggi_kalori'] = data['konsumsi_tinggi_kalori'].replace('Ya', 1)\n",
"data['konsumsi_tinggi_kalori'] = data['konsumsi_tinggi_kalori'].replace('Tidak', 0)\n",
"\n",
"data['konsumsi_sayuran'] = data['konsumsi_sayuran'].replace('Selalu', 2)\n",
"data['konsumsi_sayuran'] = data['konsumsi_sayuran'].replace('Kadang-kadang', 1)\n",
"data['konsumsi_sayuran'] = data['konsumsi_sayuran'].replace('Tidak pernah', 0)\n",
"\n",
"data['makan_berat'] = data['makan_berat'].replace('Lebih 3x', 3)\n",
"data['makan_berat'] = data['makan_berat'].replace('3x', 2)\n",
"data['makan_berat'] = data['makan_berat'].replace('1-2x', 1)\n",
"\n",
"data['ngemil'] = data['ngemil'].replace('Selalu', 3)\n",
"data['ngemil'] = data['ngemil'].replace('Sering', 2)\n",
"data['ngemil'] = data['ngemil'].replace('Kadang-kadang', 1)\n",
"data['ngemil'] = data['ngemil'].replace('Tidak pernah', 0)\n",
"\n",
"data['merokok'] = data['merokok'].replace('Ya', 1)\n",
"data['merokok'] = data['merokok'].replace('Tidak', 0)\n",
"\n",
"data['konsumsi_air_liter'] = data['konsumsi_air_liter'].replace('Lebih 2 liter', 3)\n",
"data['konsumsi_air_liter'] = data['konsumsi_air_liter'].replace('1-2 liter', 2)\n",
"data['konsumsi_air_liter'] = data['konsumsi_air_liter'].replace('Kurang 1 liter', 1)\n",
"\n",
"data['pemantauan_kalori'] = data['pemantauan_kalori'].replace('Ya', 1)\n",
"data['pemantauan_kalori'] = data['pemantauan_kalori'].replace('Tidak', 0)\n",
"\n",
"data['aktifitas_fisik'] = data['aktifitas_fisik'].replace('4-5 hari', 3)\n",
"data['aktifitas_fisik'] = data['aktifitas_fisik'].replace('2-4 hari', 2)\n",
"data['aktifitas_fisik'] = data['aktifitas_fisik'].replace('1-2 hari', 1)\n",
"data['aktifitas_fisik'] = data['aktifitas_fisik'].replace('Tidak pernah', 0)\n",
"\n",
"data['penggunaan_perangkat_teknologi'] = data['penggunaan_perangkat_teknologi'].replace('Lebih 5 jam', 3)\n",
"data['penggunaan_perangkat_teknologi'] = data['penggunaan_perangkat_teknologi'].replace('3-5 jam', 2)\n",
"data['penggunaan_perangkat_teknologi'] = data['penggunaan_perangkat_teknologi'].replace('0-2 jam', 1)\n",
"\n",
"data['konsumsi_alkohol'] = data['konsumsi_alkohol'].replace('Selalu', 3)\n",
"data['konsumsi_alkohol'] = data['konsumsi_alkohol'].replace('Sering', 2)\n",
"data['konsumsi_alkohol'] = data['konsumsi_alkohol'].replace('Kadang-kadang', 1)\n",
"data['konsumsi_alkohol'] = data['konsumsi_alkohol'].replace('Tidak pernah', 0)\n",
"\n",
"data['transporasi_biasa_digunakan'] = data['transporasi_biasa_digunakan'].replace('Mobil', 0)\n",
"data['transporasi_biasa_digunakan'] = data['transporasi_biasa_digunakan'].replace('Sepeda motor', 1)\n",
"data['transporasi_biasa_digunakan'] = data['transporasi_biasa_digunakan'].replace('Sepeda', 2)\n",
"data['transporasi_biasa_digunakan'] = data['transporasi_biasa_digunakan'].replace('Transportasi umum', 3)\n",
"data['transporasi_biasa_digunakan'] = data['transporasi_biasa_digunakan'].replace('Jalan kaki', 4)\n",
"\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "1175a8b6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 448 entries, 0 to 447\n",
"Data columns (total 17 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 jenis_kelamin 448 non-null int64 \n",
" 1 umur 448 non-null int64 \n",
" 2 tinggi_badan_meter 448 non-null float64\n",
" 3 berat_badan_kilogram 448 non-null int64 \n",
" 4 histori_keluarga_kelebihan_BB 448 non-null int64 \n",
" 5 konsumsi_tinggi_kalori 448 non-null int64 \n",
" 6 konsumsi_sayuran 448 non-null int64 \n",
" 7 makan_berat 448 non-null int64 \n",
" 8 ngemil 448 non-null int64 \n",
" 9 merokok 448 non-null int64 \n",
" 10 konsumsi_air_liter 448 non-null int64 \n",
" 11 pemantauan_kalori 448 non-null int64 \n",
" 12 aktifitas_fisik 448 non-null int64 \n",
" 13 penggunaan_perangkat_teknologi 448 non-null int64 \n",
" 14 konsumsi_alkohol 448 non-null int64 \n",
" 15 transporasi_biasa_digunakan 448 non-null int64 \n",
" 16 kelas_obesitas 448 non-null object \n",
"dtypes: float64(1), int64(15), object(1)\n",
"memory usage: 59.6+ KB\n"
]
}
],
"source": [
"data.info()"
]
},
{
"cell_type": "markdown",
"id": "61a35a3b",
"metadata": {},
"source": [
"## Menyeimbangkan kelas"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "6029b2b1",
"metadata": {},
"outputs": [],
"source": [
"X = data.drop(columns='kelas_obesitas', axis = 1)\n",
"Y = data['kelas_obesitas']"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "560df6fa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"kelebihan_berat_badan 141\n",
"normal 141\n",
"obesitas_I 141\n",
"obesitas_II 141\n",
"berat_badan_kurang 141\n",
"Name: kelas_obesitas, dtype: int64\n"
]
},
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
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"\n",
" .dataframe thead th {\n",
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>jenis_kelamin</th>\n",
" <th>umur</th>\n",
" <th>tinggi_badan_meter</th>\n",
" <th>berat_badan_kilogram</th>\n",
" <th>histori_keluarga_kelebihan_BB</th>\n",
" <th>konsumsi_tinggi_kalori</th>\n",
" <th>konsumsi_sayuran</th>\n",
" <th>makan_berat</th>\n",
" <th>ngemil</th>\n",
" <th>merokok</th>\n",
" <th>konsumsi_air_liter</th>\n",
" <th>pemantauan_kalori</th>\n",
" <th>aktifitas_fisik</th>\n",
" <th>penggunaan_perangkat_teknologi</th>\n",
" <th>konsumsi_alkohol</th>\n",
" <th>transporasi_biasa_digunakan</th>\n",
" <th>kelas_obesitas</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0</td>\n",
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" <td>1.620000</td>\n",
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" <td>0</td>\n",
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" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0</td>\n",
" <td>21</td>\n",
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" <td>56</td>\n",
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" <td>1</td>\n",
" <td>1</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" <td>1.620000</td>\n",
" <td>53</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
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" <td>3</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" <td>1.640000</td>\n",
" <td>53</td>\n",
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" <td>1</td>\n",
" <td>2</td>\n",
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" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
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" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
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" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
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" <td>1</td>\n",
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" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>701</th>\n",
" <td>0</td>\n",
" <td>34</td>\n",
" <td>1.606212</td>\n",
" <td>79</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>702</th>\n",
" <td>0</td>\n",
" <td>38</td>\n",
" <td>1.545496</td>\n",
" <td>79</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>703</th>\n",
" <td>0</td>\n",
" <td>37</td>\n",
" <td>1.566180</td>\n",
" <td>80</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>704</th>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" <td>1.681425</td>\n",
" <td>90</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>705 rows × 17 columns</p>\n",
"</div>"
],
"text/plain": [
" jenis_kelamin umur tinggi_badan_meter berat_badan_kilogram \\\n",
"0 0 21 1.620000 64 \n",
"1 0 21 1.520000 56 \n",
"2 1 29 1.620000 53 \n",
"3 0 23 1.500000 55 \n",
"4 1 22 1.640000 53 \n",
".. ... ... ... ... \n",
"700 0 37 1.560000 80 \n",
"701 0 34 1.606212 79 \n",
"702 0 38 1.545496 79 \n",
"703 0 37 1.566180 80 \n",
"704 1 30 1.681425 90 \n",
"\n",
" histori_keluarga_kelebihan_BB konsumsi_tinggi_kalori konsumsi_sayuran \\\n",
"0 1 0 1 \n",
"1 1 0 2 \n",
"2 0 1 1 \n",
"3 1 1 2 \n",
"4 0 0 1 \n",
".. ... ... ... \n",
"700 1 1 2 \n",
"701 1 0 2 \n",
"702 1 1 1 \n",
"703 1 1 2 \n",
"704 1 1 2 \n",
"\n",
" makan_berat ngemil merokok konsumsi_air_liter pemantauan_kalori \\\n",
"0 2 1 0 2 0 \n",
"1 2 1 1 3 1 \n",
"2 2 1 0 2 0 \n",
"3 2 1 0 2 0 \n",
"4 2 1 0 2 0 \n",
".. ... ... ... ... ... \n",
"700 1 1 0 2 0 \n",
"701 2 1 0 2 0 \n",
"702 2 1 0 2 0 \n",
"703 1 1 0 2 0 \n",
"704 2 1 0 3 0 \n",
"\n",
" aktifitas_fisik penggunaan_perangkat_teknologi konsumsi_alkohol \\\n",
"0 0 1 0 \n",
"1 3 1 1 \n",
"2 0 1 1 \n",
"3 1 1 1 \n",
"4 3 1 1 \n",
".. ... ... ... \n",
"700 0 1 1 \n",
"701 0 1 1 \n",
"702 0 1 1 \n",
"703 1 1 1 \n",
"704 1 1 1 \n",
"\n",
" transporasi_biasa_digunakan kelas_obesitas \n",
"0 1 kelebihan_berat_badan \n",
"1 1 kelebihan_berat_badan \n",
"2 4 normal \n",
"3 3 kelebihan_berat_badan \n",
"4 1 normal \n",
".. ... ... \n",
"700 4 obesitas_II \n",
"701 2 obesitas_II \n",
"702 4 obesitas_II \n",
"703 4 obesitas_II \n",
"704 4 obesitas_II \n",
"\n",
"[705 rows x 17 columns]"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from imblearn.over_sampling import SMOTE\n",
"\n",
"smote = SMOTE(sampling_strategy='auto', random_state=0)\n",
"\n",
"X_res, y_res = smote.fit_resample(X, Y)\n",
"\n",
"data = pd.concat([X_res, y_res], axis=1)\n",
"\n",
"print(data['kelas_obesitas'].value_counts())\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "72453471",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>kelas_obesitas</th>\n",
" <th>jumlah</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>berat_badan_kurang</td>\n",
" <td>141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>normal</td>\n",
" <td>141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>obesitas_I</td>\n",
" <td>141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>obesitas_II</td>\n",
" <td>141</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" kelas_obesitas jumlah\n",
"4 berat_badan_kurang 141\n",
"1 normal 141\n",
"0 kelebihan_berat_badan 141\n",
"2 obesitas_I 141\n",
"3 obesitas_II 141"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"kelas_obesitas = data['kelas_obesitas'].value_counts().rename_axis('kelas_obesitas').reset_index(name='jumlah')\n",
"urutan_obesitas = ['berat_badan_kurang',\n",
" 'normal',\n",
" 'kelebihan_berat_badan',\n",
" 'obesitas_I',\n",
" 'obesitas_II']\n",
"kelas_obesitas['kelas_obesitas'] = pd.Categorical(kelas_obesitas['kelas_obesitas'], categories=urutan_obesitas, ordered=True)\n",
"kelas_obesitas = kelas_obesitas.sort_values(by='kelas_obesitas')\n",
"kelas_obesitas"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "fd5717da",
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 500x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(5, 5))\n",
"colors = sns.color_palette('pastel')\n",
"\n",
"plt.pie(kelas_obesitas['jumlah'], labels=kelas_obesitas['kelas_obesitas'], autopct='%1.1f%%', colors=colors)\n",
"\n",
"plt.title('Perbandingan Persentase Kelas Obesitas')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "64996edd",
"metadata": {},
"source": [
"### download data yang telah di-SMOTE"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "7a6b3dea",
"metadata": {},
"outputs": [],
"source": [
"# excel_file = pd.ExcelWriter(\"smote_full_data_obesitas.xlsx\")\n",
"# data.to_excel(excel_file, index=False)\n",
"# excel_file.save()"
]
},
{
"cell_type": "markdown",
"id": "bae7ae5a",
"metadata": {},
"source": [
"### rasio"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "13ca1902",
"metadata": {},
"outputs": [],
"source": [
"test_size = 0.02"
]
},
{
"cell_type": "markdown",
"id": "4afc40d8",
"metadata": {},
"source": [
"### Siap kan data untuk ditampilkan pada sistem"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "8f5ef97b",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>jenis_kelamin</th>\n",
" <th>umur</th>\n",
" <th>tinggi_badan_meter</th>\n",
" <th>berat_badan_kilogram</th>\n",
" <th>histori_keluarga_kelebihan_BB</th>\n",
" <th>konsumsi_tinggi_kalori</th>\n",
" <th>konsumsi_sayuran</th>\n",
" <th>makan_berat</th>\n",
" <th>ngemil</th>\n",
" <th>merokok</th>\n",
" <th>konsumsi_air_liter</th>\n",
" <th>pemantauan_kalori</th>\n",
" <th>aktifitas_fisik</th>\n",
" <th>penggunaan_perangkat_teknologi</th>\n",
" <th>konsumsi_alkohol</th>\n",
" <th>transporasi_biasa_digunakan</th>\n",
" <th>kelas_obesitas</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0</td>\n",
" <td>21</td>\n",
" <td>1.620000</td>\n",
" <td>64</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0</td>\n",
" <td>21</td>\n",
" <td>1.520000</td>\n",
" <td>56</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" <td>1.620000</td>\n",
" <td>53</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0</td>\n",
" <td>23</td>\n",
" <td>1.500000</td>\n",
" <td>55</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" <td>1.640000</td>\n",
" <td>53</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>700</th>\n",
" <td>0</td>\n",
" <td>37</td>\n",
" <td>1.560000</td>\n",
" <td>80</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>701</th>\n",
" <td>0</td>\n",
" <td>34</td>\n",
" <td>1.606212</td>\n",
" <td>79</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>702</th>\n",
" <td>0</td>\n",
" <td>38</td>\n",
" <td>1.545496</td>\n",
" <td>79</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>703</th>\n",
" <td>0</td>\n",
" <td>37</td>\n",
" <td>1.566180</td>\n",
" <td>80</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>704</th>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" <td>1.681425</td>\n",
" <td>90</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>705 rows × 17 columns</p>\n",
"</div>"
],
"text/plain": [
" jenis_kelamin umur tinggi_badan_meter berat_badan_kilogram \\\n",
"0 0 21 1.620000 64 \n",
"1 0 21 1.520000 56 \n",
"2 1 29 1.620000 53 \n",
"3 0 23 1.500000 55 \n",
"4 1 22 1.640000 53 \n",
".. ... ... ... ... \n",
"700 0 37 1.560000 80 \n",
"701 0 34 1.606212 79 \n",
"702 0 38 1.545496 79 \n",
"703 0 37 1.566180 80 \n",
"704 1 30 1.681425 90 \n",
"\n",
" histori_keluarga_kelebihan_BB konsumsi_tinggi_kalori konsumsi_sayuran \\\n",
"0 1 0 1 \n",
"1 1 0 2 \n",
"2 0 1 1 \n",
"3 1 1 2 \n",
"4 0 0 1 \n",
".. ... ... ... \n",
"700 1 1 2 \n",
"701 1 0 2 \n",
"702 1 1 1 \n",
"703 1 1 2 \n",
"704 1 1 2 \n",
"\n",
" makan_berat ngemil merokok konsumsi_air_liter pemantauan_kalori \\\n",
"0 2 1 0 2 0 \n",
"1 2 1 1 3 1 \n",
"2 2 1 0 2 0 \n",
"3 2 1 0 2 0 \n",
"4 2 1 0 2 0 \n",
".. ... ... ... ... ... \n",
"700 1 1 0 2 0 \n",
"701 2 1 0 2 0 \n",
"702 2 1 0 2 0 \n",
"703 1 1 0 2 0 \n",
"704 2 1 0 3 0 \n",
"\n",
" aktifitas_fisik penggunaan_perangkat_teknologi konsumsi_alkohol \\\n",
"0 0 1 0 \n",
"1 3 1 1 \n",
"2 0 1 1 \n",
"3 1 1 1 \n",
"4 3 1 1 \n",
".. ... ... ... \n",
"700 0 1 1 \n",
"701 0 1 1 \n",
"702 0 1 1 \n",
"703 1 1 1 \n",
"704 1 1 1 \n",
"\n",
" transporasi_biasa_digunakan kelas_obesitas \n",
"0 1 kelebihan_berat_badan \n",
"1 1 kelebihan_berat_badan \n",
"2 4 normal \n",
"3 3 kelebihan_berat_badan \n",
"4 1 normal \n",
".. ... ... \n",
"700 4 obesitas_II \n",
"701 2 obesitas_II \n",
"702 4 obesitas_II \n",
"703 4 obesitas_II \n",
"704 4 obesitas_II \n",
"\n",
"[705 rows x 17 columns]"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_baru = data.copy()\n",
"data_baru"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "e5fffcfe",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>jenis_kelamin</th>\n",
" <th>umur</th>\n",
" <th>tinggi_badan_meter</th>\n",
" <th>berat_badan_kilogram</th>\n",
" <th>histori_keluarga_kelebihan_BB</th>\n",
" <th>konsumsi_tinggi_kalori</th>\n",
" <th>konsumsi_sayuran</th>\n",
" <th>makan_berat</th>\n",
" <th>ngemil</th>\n",
" <th>merokok</th>\n",
" <th>konsumsi_air_liter</th>\n",
" <th>pemantauan_kalori</th>\n",
" <th>aktifitas_fisik</th>\n",
" <th>penggunaan_perangkat_teknologi</th>\n",
" <th>konsumsi_alkohol</th>\n",
" <th>transporasi_biasa_digunakan</th>\n",
" <th>kelas_obesitas</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.620000</td>\n",
" <td>64</td>\n",
" <td>Ya</td>\n",
" <td>Tidak</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.520000</td>\n",
" <td>56</td>\n",
" <td>Ya</td>\n",
" <td>Tidak</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Ya</td>\n",
" <td>Lebih 2 liter</td>\n",
" <td>Ya</td>\n",
" <td>4-5 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Laki-laki</td>\n",
" <td>29</td>\n",
" <td>1.620000</td>\n",
" <td>53</td>\n",
" <td>Tidak</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Perempuan</td>\n",
" <td>23</td>\n",
" <td>1.500000</td>\n",
" <td>55</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Transportasi umum</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Laki-laki</td>\n",
" <td>22</td>\n",
" <td>1.640000</td>\n",
" <td>53</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>4-5 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>700</th>\n",
" <td>Perempuan</td>\n",
" <td>37</td>\n",
" <td>1.560000</td>\n",
" <td>80</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>701</th>\n",
" <td>Perempuan</td>\n",
" <td>34</td>\n",
" <td>1.606212</td>\n",
" <td>79</td>\n",
" <td>Ya</td>\n",
" <td>Tidak</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>702</th>\n",
" <td>Perempuan</td>\n",
" <td>38</td>\n",
" <td>1.545496</td>\n",
" <td>79</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>703</th>\n",
" <td>Perempuan</td>\n",
" <td>37</td>\n",
" <td>1.566180</td>\n",
" <td>80</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>704</th>\n",
" <td>Laki-laki</td>\n",
" <td>30</td>\n",
" <td>1.681425</td>\n",
" <td>90</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>Lebih 2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>705 rows × 17 columns</p>\n",
"</div>"
],
"text/plain": [
" jenis_kelamin umur tinggi_badan_meter berat_badan_kilogram \\\n",
"0 Perempuan 21 1.620000 64 \n",
"1 Perempuan 21 1.520000 56 \n",
"2 Laki-laki 29 1.620000 53 \n",
"3 Perempuan 23 1.500000 55 \n",
"4 Laki-laki 22 1.640000 53 \n",
".. ... ... ... ... \n",
"700 Perempuan 37 1.560000 80 \n",
"701 Perempuan 34 1.606212 79 \n",
"702 Perempuan 38 1.545496 79 \n",
"703 Perempuan 37 1.566180 80 \n",
"704 Laki-laki 30 1.681425 90 \n",
"\n",
" histori_keluarga_kelebihan_BB konsumsi_tinggi_kalori konsumsi_sayuran \\\n",
"0 Ya Tidak Kadang-kadang \n",
"1 Ya Tidak Selalu \n",
"2 Tidak Ya Kadang-kadang \n",
"3 Ya Ya Selalu \n",
"4 Tidak Tidak Kadang-kadang \n",
".. ... ... ... \n",
"700 Ya Ya Selalu \n",
"701 Ya Tidak Selalu \n",
"702 Ya Ya Kadang-kadang \n",
"703 Ya Ya Selalu \n",
"704 Ya Ya Selalu \n",
"\n",
" makan_berat ngemil merokok konsumsi_air_liter pemantauan_kalori \\\n",
"0 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"1 3x Kadang-kadang Ya Lebih 2 liter Ya \n",
"2 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"3 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"4 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
".. ... ... ... ... ... \n",
"700 1-2x Kadang-kadang Tidak 1-2 liter Tidak \n",
"701 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"702 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"703 1-2x Kadang-kadang Tidak 1-2 liter Tidak \n",
"704 3x Kadang-kadang Tidak Lebih 2 liter Tidak \n",
"\n",
" aktifitas_fisik penggunaan_perangkat_teknologi konsumsi_alkohol \\\n",
"0 Tidak pernah 0-2 jam Tidak pernah \n",
"1 4-5 hari 0-2 jam Kadang-kadang \n",
"2 Tidak pernah 0-2 jam Kadang-kadang \n",
"3 1-2 hari 0-2 jam Kadang-kadang \n",
"4 4-5 hari 0-2 jam Kadang-kadang \n",
".. ... ... ... \n",
"700 Tidak pernah 0-2 jam Kadang-kadang \n",
"701 Tidak pernah 0-2 jam Kadang-kadang \n",
"702 Tidak pernah 0-2 jam Kadang-kadang \n",
"703 1-2 hari 0-2 jam Kadang-kadang \n",
"704 1-2 hari 0-2 jam Kadang-kadang \n",
"\n",
" transporasi_biasa_digunakan kelas_obesitas \n",
"0 Sepeda motor kelebihan_berat_badan \n",
"1 Sepeda motor kelebihan_berat_badan \n",
"2 Jalan kaki normal \n",
"3 Transportasi umum kelebihan_berat_badan \n",
"4 Sepeda motor normal \n",
".. ... ... \n",
"700 Jalan kaki obesitas_II \n",
"701 Sepeda obesitas_II \n",
"702 Jalan kaki obesitas_II \n",
"703 Jalan kaki obesitas_II \n",
"704 Jalan kaki obesitas_II \n",
"\n",
"[705 rows x 17 columns]"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_baru['jenis_kelamin'] = data_baru['jenis_kelamin'].replace(1, 'Laki-laki')\n",
"data_baru['jenis_kelamin'] = data_baru['jenis_kelamin'].replace(0, 'Perempuan')\n",
"\n",
"data_baru['histori_keluarga_kelebihan_BB'] = data_baru['histori_keluarga_kelebihan_BB'].replace(1, 'Ya')\n",
"data_baru['histori_keluarga_kelebihan_BB'] = data_baru['histori_keluarga_kelebihan_BB'].replace(0, 'Tidak')\n",
"\n",
"data_baru['konsumsi_tinggi_kalori'] = data_baru['konsumsi_tinggi_kalori'].replace(1, 'Ya')\n",
"data_baru['konsumsi_tinggi_kalori'] = data_baru['konsumsi_tinggi_kalori'].replace(0, 'Tidak')\n",
"\n",
"data_baru['konsumsi_sayuran'] = data_baru['konsumsi_sayuran'].replace(2, 'Selalu')\n",
"data_baru['konsumsi_sayuran'] = data_baru['konsumsi_sayuran'].replace(1, 'Kadang-kadang')\n",
"data_baru['konsumsi_sayuran'] = data_baru['konsumsi_sayuran'].replace(0, 'Tidak pernah')\n",
"\n",
"data_baru['makan_berat'] = data_baru['makan_berat'].replace(3, 'Lebih 3x')\n",
"data_baru['makan_berat'] = data_baru['makan_berat'].replace(2, '3x')\n",
"data_baru['makan_berat'] = data_baru['makan_berat'].replace(1, '1-2x')\n",
"\n",
"data_baru['ngemil'] = data_baru['ngemil'].replace(3, 'Selalu')\n",
"data_baru['ngemil'] = data_baru['ngemil'].replace(2, 'Sering')\n",
"data_baru['ngemil'] = data_baru['ngemil'].replace(1, 'Kadang-kadang')\n",
"data_baru['ngemil'] = data_baru['ngemil'].replace(0, 'Tidak pernah')\n",
"\n",
"data_baru['merokok'] = data_baru['merokok'].replace(1, 'Ya')\n",
"data_baru['merokok'] = data_baru['merokok'].replace(0, 'Tidak')\n",
"\n",
"data_baru['konsumsi_air_liter'] = data_baru['konsumsi_air_liter'].replace(3, 'Lebih 2 liter')\n",
"data_baru['konsumsi_air_liter'] = data_baru['konsumsi_air_liter'].replace(2, '1-2 liter')\n",
"data_baru['konsumsi_air_liter'] = data_baru['konsumsi_air_liter'].replace(1, 'Kurang 1 liter')\n",
"\n",
"data_baru['pemantauan_kalori'] = data_baru['pemantauan_kalori'].replace(1, 'Ya')\n",
"data_baru['pemantauan_kalori'] = data_baru['pemantauan_kalori'].replace(0, 'Tidak')\n",
"\n",
"data_baru['aktifitas_fisik'] = data_baru['aktifitas_fisik'].replace(3, '4-5 hari')\n",
"data_baru['aktifitas_fisik'] = data_baru['aktifitas_fisik'].replace(2, '2-4 hari')\n",
"data_baru['aktifitas_fisik'] = data_baru['aktifitas_fisik'].replace(1, '1-2 hari')\n",
"data_baru['aktifitas_fisik'] = data_baru['aktifitas_fisik'].replace(0, 'Tidak pernah')\n",
"\n",
"data_baru['penggunaan_perangkat_teknologi'] = data_baru['penggunaan_perangkat_teknologi'].replace(3, 'Lebih 5 jam')\n",
"data_baru['penggunaan_perangkat_teknologi'] = data_baru['penggunaan_perangkat_teknologi'].replace(2, '3-5 jam')\n",
"data_baru['penggunaan_perangkat_teknologi'] = data_baru['penggunaan_perangkat_teknologi'].replace(1, '0-2 jam')\n",
"\n",
"data_baru['konsumsi_alkohol'] = data_baru['konsumsi_alkohol'].replace(3, 'Selalu')\n",
"data_baru['konsumsi_alkohol'] = data_baru['konsumsi_alkohol'].replace(2, 'Sering')\n",
"data_baru['konsumsi_alkohol'] = data_baru['konsumsi_alkohol'].replace(1, 'Kadang-kadang')\n",
"data_baru['konsumsi_alkohol'] = data_baru['konsumsi_alkohol'].replace(0, 'Tidak pernah')\n",
"\n",
"data_baru['transporasi_biasa_digunakan'] = data_baru['transporasi_biasa_digunakan'].replace(0, 'Mobil')\n",
"data_baru['transporasi_biasa_digunakan'] = data_baru['transporasi_biasa_digunakan'].replace(1, 'Sepeda motor')\n",
"data_baru['transporasi_biasa_digunakan'] = data_baru['transporasi_biasa_digunakan'].replace(2, 'Sepeda')\n",
"data_baru['transporasi_biasa_digunakan'] = data_baru['transporasi_biasa_digunakan'].replace(3, 'Transportasi umum')\n",
"data_baru['transporasi_biasa_digunakan'] = data_baru['transporasi_biasa_digunakan'].replace(4, 'Jalan kaki')\n",
"\n",
"data_baru"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "618d2003",
"metadata": {},
"outputs": [],
"source": [
"Xbaru = data_baru.drop(columns='kelas_obesitas', axis = 1)\n",
"Ybaru = data_baru['kelas_obesitas']\n",
"X_trainbaru, X_testbaru, Y_trainbaru, Y_testbaru = train_test_split(data_baru, data_baru, test_size = test_size, stratify = Ybaru, random_state = 0)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "545515bd",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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"<div>\n",
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"\n",
" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>jenis_kelamin</th>\n",
" <th>umur</th>\n",
" <th>tinggi_badan_meter</th>\n",
" <th>berat_badan_kilogram</th>\n",
" <th>histori_keluarga_kelebihan_BB</th>\n",
" <th>konsumsi_tinggi_kalori</th>\n",
" <th>konsumsi_sayuran</th>\n",
" <th>makan_berat</th>\n",
" <th>ngemil</th>\n",
" <th>merokok</th>\n",
" <th>konsumsi_air_liter</th>\n",
" <th>pemantauan_kalori</th>\n",
" <th>aktifitas_fisik</th>\n",
" <th>penggunaan_perangkat_teknologi</th>\n",
" <th>konsumsi_alkohol</th>\n",
" <th>transporasi_biasa_digunakan</th>\n",
" <th>kelas_obesitas</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>167</th>\n",
" <td>Perempuan</td>\n",
" <td>23</td>\n",
" <td>1.700000</td>\n",
" <td>56</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak</td>\n",
" <td>Selalu</td>\n",
" <td>Lebih 3x</td>\n",
" <td>Selalu</td>\n",
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" <td>Lebih 2 liter</td>\n",
" <td>Ya</td>\n",
" <td>4-5 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Jalan kaki</td>\n",
" <td>normal</td>\n",
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" <tr>\n",
" <th>101</th>\n",
" <td>Perempuan</td>\n",
" <td>41</td>\n",
" <td>1.540000</td>\n",
" <td>80</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Selalu</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>680</th>\n",
" <td>Perempuan</td>\n",
" <td>37</td>\n",
" <td>1.500000</td>\n",
" <td>75</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Transportasi umum</td>\n",
" <td>obesitas_II</td>\n",
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" <tr>\n",
" <th>271</th>\n",
" <td>Perempuan</td>\n",
" <td>19</td>\n",
" <td>1.540000</td>\n",
" <td>42</td>\n",
" <td>Tidak</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Sering</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>529</th>\n",
" <td>Perempuan</td>\n",
" <td>20</td>\n",
" <td>1.572607</td>\n",
" <td>59</td>\n",
" <td>Tidak</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>1-2x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>kelebihan_berat_badan</td>\n",
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" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <tr>\n",
" <th>285</th>\n",
" <td>Perempuan</td>\n",
" <td>20</td>\n",
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" <td>49</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>Lebih 3x</td>\n",
" <td>Sering</td>\n",
" <td>Tidak</td>\n",
" <td>Lebih 2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>2-4 hari</td>\n",
" <td>0-2 jam</td>\n",
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" <td>Tidak</td>\n",
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" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>2-4 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>normal</td>\n",
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" <td>1.650000</td>\n",
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" <td>Tidak</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Lebih 3x</td>\n",
" <td>Sering</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
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" <td>0-2 jam</td>\n",
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" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.620000</td>\n",
" <td>64</td>\n",
" <td>Ya</td>\n",
" <td>Tidak</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>kelebihan_berat_badan</td>\n",
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" <tr>\n",
" <th>585</th>\n",
" <td>Perempuan</td>\n",
" <td>33</td>\n",
" <td>1.680000</td>\n",
" <td>77</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_I</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>690 rows × 17 columns</p>\n",
"</div>"
],
"text/plain": [
" jenis_kelamin umur tinggi_badan_meter berat_badan_kilogram \\\n",
"167 Perempuan 23 1.700000 56 \n",
"101 Perempuan 41 1.540000 80 \n",
"680 Perempuan 37 1.500000 75 \n",
"271 Perempuan 19 1.540000 42 \n",
"529 Perempuan 20 1.572607 59 \n",
".. ... ... ... ... \n",
"285 Perempuan 20 1.670000 49 \n",
"151 Perempuan 21 1.530000 53 \n",
"15 Laki-laki 22 1.650000 62 \n",
"0 Perempuan 21 1.620000 64 \n",
"585 Perempuan 33 1.680000 77 \n",
"\n",
" histori_keluarga_kelebihan_BB konsumsi_tinggi_kalori konsumsi_sayuran \\\n",
"167 Tidak Tidak Selalu \n",
"101 Ya Ya Kadang-kadang \n",
"680 Ya Ya Kadang-kadang \n",
"271 Tidak Ya Selalu \n",
"529 Tidak Ya Kadang-kadang \n",
".. ... ... ... \n",
"285 Ya Ya Selalu \n",
"151 Tidak Ya Selalu \n",
"15 Tidak Ya Kadang-kadang \n",
"0 Ya Tidak Kadang-kadang \n",
"585 Ya Ya Selalu \n",
"\n",
" makan_berat ngemil merokok konsumsi_air_liter pemantauan_kalori \\\n",
"167 Lebih 3x Selalu Tidak Lebih 2 liter Ya \n",
"101 3x Selalu Tidak 1-2 liter Tidak \n",
"680 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"271 1-2x Sering Tidak 1-2 liter Tidak \n",
"529 1-2x Kadang-kadang Tidak 1-2 liter Tidak \n",
".. ... ... ... ... ... \n",
"285 Lebih 3x Sering Tidak Lebih 2 liter Tidak \n",
"151 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"15 Lebih 3x Sering Tidak 1-2 liter Tidak \n",
"0 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"585 1-2x Kadang-kadang Tidak 1-2 liter Tidak \n",
"\n",
" aktifitas_fisik penggunaan_perangkat_teknologi konsumsi_alkohol \\\n",
"167 4-5 hari 0-2 jam Tidak pernah \n",
"101 Tidak pernah 0-2 jam Kadang-kadang \n",
"680 Tidak pernah 0-2 jam Kadang-kadang \n",
"271 1-2 hari 0-2 jam Kadang-kadang \n",
"529 Tidak pernah 0-2 jam Tidak pernah \n",
".. ... ... ... \n",
"285 2-4 hari 0-2 jam Tidak pernah \n",
"151 2-4 hari 0-2 jam Kadang-kadang \n",
"15 2-4 hari 0-2 jam Kadang-kadang \n",
"0 Tidak pernah 0-2 jam Tidak pernah \n",
"585 Tidak pernah 0-2 jam Tidak pernah \n",
"\n",
" transporasi_biasa_digunakan kelas_obesitas \n",
"167 Jalan kaki normal \n",
"101 Jalan kaki obesitas_II \n",
"680 Transportasi umum obesitas_II \n",
"271 Sepeda motor berat_badan_kurang \n",
"529 Sepeda motor kelebihan_berat_badan \n",
".. ... ... \n",
"285 Sepeda motor berat_badan_kurang \n",
"151 Sepeda motor normal \n",
"15 Sepeda motor normal \n",
"0 Sepeda motor kelebihan_berat_badan \n",
"585 Jalan kaki obesitas_I \n",
"\n",
"[690 rows x 17 columns]"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X_trainbaru"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "e7332fae",
"metadata": {
"scrolled": true
},
"outputs": [
{
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" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>173</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.540000</td>\n",
" <td>47</td>\n",
" <td>Ya</td>\n",
" <td>Tidak</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Selalu</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>2-4 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>510</th>\n",
" <td>Perempuan</td>\n",
" <td>25</td>\n",
" <td>1.643548</td>\n",
" <td>62</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Mobil</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>548</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.641347</td>\n",
" <td>66</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>389</th>\n",
" <td>Laki-laki</td>\n",
" <td>39</td>\n",
" <td>1.720000</td>\n",
" <td>86</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_I</td>\n",
" </tr>\n",
" <tr>\n",
" <th>394</th>\n",
" <td>Perempuan</td>\n",
" <td>37</td>\n",
" <td>1.560000</td>\n",
" <td>77</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>206</th>\n",
" <td>Perempuan</td>\n",
" <td>18</td>\n",
" <td>1.640000</td>\n",
" <td>59</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>295</th>\n",
" <td>Perempuan</td>\n",
" <td>19</td>\n",
" <td>1.680000</td>\n",
" <td>49</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>480</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.694749</td>\n",
" <td>49</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Sering</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>124</th>\n",
" <td>Perempuan</td>\n",
" <td>20</td>\n",
" <td>1.630000</td>\n",
" <td>64</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Tidak pernah</td>\n",
" <td>3x</td>\n",
" <td>Selalu</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>3-5 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Jalan kaki</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" jenis_kelamin umur tinggi_badan_meter berat_badan_kilogram \\\n",
"606 Perempuan 31 1.672625 71 \n",
"71 Perempuan 19 1.650000 56 \n",
"609 Perempuan 39 1.711621 84 \n",
"678 Perempuan 37 1.560000 79 \n",
"644 Perempuan 39 1.528746 79 \n",
"275 Perempuan 20 1.550000 41 \n",
"173 Perempuan 21 1.540000 47 \n",
"510 Perempuan 25 1.643548 62 \n",
"548 Perempuan 21 1.641347 66 \n",
"389 Laki-laki 39 1.720000 86 \n",
"394 Perempuan 37 1.560000 77 \n",
"206 Perempuan 18 1.640000 59 \n",
"295 Perempuan 19 1.680000 49 \n",
"480 Perempuan 21 1.694749 49 \n",
"124 Perempuan 20 1.630000 64 \n",
"\n",
" histori_keluarga_kelebihan_BB konsumsi_tinggi_kalori konsumsi_sayuran \\\n",
"606 Ya Ya Kadang-kadang \n",
"71 Ya Ya Selalu \n",
"609 Tidak Ya Selalu \n",
"678 Ya Ya Kadang-kadang \n",
"644 Ya Ya Kadang-kadang \n",
"275 Tidak Ya Selalu \n",
"173 Ya Tidak Selalu \n",
"510 Tidak Tidak Kadang-kadang \n",
"548 Ya Ya Selalu \n",
"389 Ya Ya Selalu \n",
"394 Ya Ya Kadang-kadang \n",
"206 Ya Ya Kadang-kadang \n",
"295 Tidak Tidak Selalu \n",
"480 Ya Ya Selalu \n",
"124 Ya Ya Tidak pernah \n",
"\n",
" makan_berat ngemil merokok konsumsi_air_liter pemantauan_kalori \\\n",
"606 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"71 3x Sering Ya Lebih 2 liter Ya \n",
"609 1-2x Kadang-kadang Tidak Lebih 2 liter Tidak \n",
"678 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"644 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"275 1-2x Sering Tidak 1-2 liter Tidak \n",
"173 3x Selalu Tidak 1-2 liter Tidak \n",
"510 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"548 1-2x Kadang-kadang Tidak 1-2 liter Tidak \n",
"389 1-2x Kadang-kadang Tidak 1-2 liter Tidak \n",
"394 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"206 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"295 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"480 3x Sering Tidak 1-2 liter Tidak \n",
"124 3x Selalu Tidak 1-2 liter Tidak \n",
"\n",
" aktifitas_fisik penggunaan_perangkat_teknologi konsumsi_alkohol \\\n",
"606 Tidak pernah 0-2 jam Kadang-kadang \n",
"71 1-2 hari 3-5 jam Sering \n",
"609 Tidak pernah 0-2 jam Tidak pernah \n",
"678 Tidak pernah 0-2 jam Kadang-kadang \n",
"644 Tidak pernah 0-2 jam Kadang-kadang \n",
"275 Tidak pernah 0-2 jam Kadang-kadang \n",
"173 2-4 hari 0-2 jam Tidak pernah \n",
"510 1-2 hari 0-2 jam Tidak pernah \n",
"548 Tidak pernah 0-2 jam Tidak pernah \n",
"389 Tidak pernah 0-2 jam Tidak pernah \n",
"394 Tidak pernah 0-2 jam Kadang-kadang \n",
"206 1-2 hari 0-2 jam Kadang-kadang \n",
"295 1-2 hari 0-2 jam Kadang-kadang \n",
"480 Tidak pernah 0-2 jam Tidak pernah \n",
"124 Tidak pernah 3-5 jam Tidak pernah \n",
"\n",
" transporasi_biasa_digunakan kelas_obesitas \n",
"606 Jalan kaki obesitas_I \n",
"71 Sepeda motor normal \n",
"609 Jalan kaki obesitas_I \n",
"678 Jalan kaki obesitas_II \n",
"644 Jalan kaki obesitas_II \n",
"275 Sepeda motor berat_badan_kurang \n",
"173 Sepeda motor normal \n",
"510 Mobil kelebihan_berat_badan \n",
"548 Sepeda motor kelebihan_berat_badan \n",
"389 Jalan kaki obesitas_I \n",
"394 Jalan kaki obesitas_II \n",
"206 Sepeda motor normal \n",
"295 Sepeda motor berat_badan_kurang \n",
"480 Sepeda motor berat_badan_kurang \n",
"124 Jalan kaki kelebihan_berat_badan "
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X_testbaru"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "a5fe3aac",
"metadata": {},
"outputs": [],
"source": [
"# excel_file = pd.ExcelWriter(\"smote_training_data_obesitas_baru.xlsx\")\n",
"# X_trainbaru.to_excel(excel_file)\n",
"# excel_file.save()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "9d273e8a",
"metadata": {},
"outputs": [],
"source": [
"# excel_file = pd.ExcelWriter(\"smote_testing_data_obesitas_baru.xlsx\")\n",
"# X_testbaru.to_excel(excel_file)\n",
"# excel_file.save()"
]
},
{
"cell_type": "markdown",
"id": "c13fd6bc",
"metadata": {},
"source": [
"### Siap kan data untuk perhitungan manual"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "5e1f265f",
"metadata": {},
"outputs": [],
"source": [
"Y = data['kelas_obesitas']\n",
"X_trainhitung, X_testhitung, Y_trainhitung, Y_testhitung = train_test_split(data, data, test_size = test_size, stratify = Y, random_state = 0)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "31943e9b",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>jenis_kelamin</th>\n",
" <th>umur</th>\n",
" <th>tinggi_badan_meter</th>\n",
" <th>berat_badan_kilogram</th>\n",
" <th>histori_keluarga_kelebihan_BB</th>\n",
" <th>konsumsi_tinggi_kalori</th>\n",
" <th>konsumsi_sayuran</th>\n",
" <th>makan_berat</th>\n",
" <th>ngemil</th>\n",
" <th>merokok</th>\n",
" <th>konsumsi_air_liter</th>\n",
" <th>pemantauan_kalori</th>\n",
" <th>aktifitas_fisik</th>\n",
" <th>penggunaan_perangkat_teknologi</th>\n",
" <th>konsumsi_alkohol</th>\n",
" <th>transporasi_biasa_digunakan</th>\n",
" <th>kelas_obesitas</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>271</th>\n",
" <td>0</td>\n",
" <td>19</td>\n",
" <td>1.540000</td>\n",
" <td>42</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
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" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>309</th>\n",
" <td>0</td>\n",
" <td>19</td>\n",
" <td>1.580000</td>\n",
" <td>44</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>266</th>\n",
" <td>0</td>\n",
" <td>19</td>\n",
" <td>1.530000</td>\n",
" <td>42</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>303</th>\n",
" <td>0</td>\n",
" <td>20</td>\n",
" <td>1.520000</td>\n",
" <td>42</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>291</th>\n",
" <td>0</td>\n",
" <td>20</td>\n",
" <td>1.520000</td>\n",
" <td>42</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>496</th>\n",
" <td>0</td>\n",
" <td>36</td>\n",
" <td>1.645857</td>\n",
" <td>48</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>454</th>\n",
" <td>0</td>\n",
" <td>21</td>\n",
" <td>1.673182</td>\n",
" <td>49</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>227</th>\n",
" <td>0</td>\n",
" <td>19</td>\n",
" <td>1.540000</td>\n",
" <td>42</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>273</th>\n",
" <td>0</td>\n",
" <td>21</td>\n",
" <td>1.670000</td>\n",
" <td>49</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>285</th>\n",
" <td>0</td>\n",
" <td>20</td>\n",
" <td>1.670000</td>\n",
" <td>49</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>138 rows × 17 columns</p>\n",
"</div>"
],
"text/plain": [
" jenis_kelamin umur tinggi_badan_meter berat_badan_kilogram \\\n",
"271 0 19 1.540000 42 \n",
"309 0 19 1.580000 44 \n",
"266 0 19 1.530000 42 \n",
"303 0 20 1.520000 42 \n",
"291 0 20 1.520000 42 \n",
".. ... ... ... ... \n",
"496 0 36 1.645857 48 \n",
"454 0 21 1.673182 49 \n",
"227 0 19 1.540000 42 \n",
"273 0 21 1.670000 49 \n",
"285 0 20 1.670000 49 \n",
"\n",
" histori_keluarga_kelebihan_BB konsumsi_tinggi_kalori konsumsi_sayuran \\\n",
"271 0 1 2 \n",
"309 0 0 2 \n",
"266 0 0 2 \n",
"303 0 1 2 \n",
"291 0 1 2 \n",
".. ... ... ... \n",
"496 0 1 2 \n",
"454 1 1 2 \n",
"227 0 1 2 \n",
"273 1 1 2 \n",
"285 1 1 2 \n",
"\n",
" makan_berat ngemil merokok konsumsi_air_liter pemantauan_kalori \\\n",
"271 1 2 0 2 0 \n",
"309 2 2 0 2 1 \n",
"266 1 2 0 2 0 \n",
"303 1 2 0 2 0 \n",
"291 1 2 0 2 0 \n",
".. ... ... ... ... ... \n",
"496 3 2 0 2 0 \n",
"454 2 2 0 3 0 \n",
"227 1 1 0 2 0 \n",
"273 2 2 0 3 0 \n",
"285 3 2 0 3 0 \n",
"\n",
" aktifitas_fisik penggunaan_perangkat_teknologi konsumsi_alkohol \\\n",
"271 1 1 1 \n",
"309 0 1 1 \n",
"266 1 1 1 \n",
"303 0 1 1 \n",
"291 0 1 1 \n",
".. ... ... ... \n",
"496 0 1 0 \n",
"454 0 1 0 \n",
"227 0 1 0 \n",
"273 0 1 0 \n",
"285 2 1 0 \n",
"\n",
" transporasi_biasa_digunakan kelas_obesitas \n",
"271 1 berat_badan_kurang \n",
"309 1 berat_badan_kurang \n",
"266 1 berat_badan_kurang \n",
"303 1 berat_badan_kurang \n",
"291 1 berat_badan_kurang \n",
".. ... ... \n",
"496 1 berat_badan_kurang \n",
"454 1 berat_badan_kurang \n",
"227 1 berat_badan_kurang \n",
"273 1 berat_badan_kurang \n",
"285 1 berat_badan_kurang \n",
"\n",
"[138 rows x 17 columns]"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_pilih_kelas = X_trainhitung[X_trainhitung['kelas_obesitas'] == 'berat_badan_kurang']\n",
"data_pilih_kelas"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "048039cd",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>jenis_kelamin</th>\n",
" <th>umur</th>\n",
" <th>tinggi_badan_meter</th>\n",
" <th>berat_badan_kilogram</th>\n",
" <th>histori_keluarga_kelebihan_BB</th>\n",
" <th>konsumsi_tinggi_kalori</th>\n",
" <th>konsumsi_sayuran</th>\n",
" <th>makan_berat</th>\n",
" <th>ngemil</th>\n",
" <th>merokok</th>\n",
" <th>konsumsi_air_liter</th>\n",
" <th>pemantauan_kalori</th>\n",
" <th>aktifitas_fisik</th>\n",
" <th>penggunaan_perangkat_teknologi</th>\n",
" <th>konsumsi_alkohol</th>\n",
" <th>transporasi_biasa_digunakan</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>138.000000</td>\n",
" <td>138.000000</td>\n",
" <td>138.000000</td>\n",
" <td>138.000000</td>\n",
" <td>138.000000</td>\n",
" <td>138.000000</td>\n",
" <td>138.000000</td>\n",
" <td>138.000000</td>\n",
" <td>138.000000</td>\n",
" <td>138.000000</td>\n",
" <td>138.000000</td>\n",
" <td>138.000000</td>\n",
" <td>138.000000</td>\n",
" <td>138.000000</td>\n",
" <td>138.000000</td>\n",
" <td>138.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>0.130435</td>\n",
" <td>20.115942</td>\n",
" <td>1.621892</td>\n",
" <td>46.065217</td>\n",
" <td>0.224638</td>\n",
" <td>0.644928</td>\n",
" <td>1.753623</td>\n",
" <td>1.891304</td>\n",
" <td>1.601449</td>\n",
" <td>0.007246</td>\n",
" <td>2.297101</td>\n",
" <td>0.072464</td>\n",
" <td>0.572464</td>\n",
" <td>1.021739</td>\n",
" <td>0.666667</td>\n",
" <td>1.021739</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>0.338008</td>\n",
" <td>3.582342</td>\n",
" <td>0.068071</td>\n",
" <td>3.765395</td>\n",
" <td>0.418864</td>\n",
" <td>0.480279</td>\n",
" <td>0.480444</td>\n",
" <td>0.751493</td>\n",
" <td>0.534091</td>\n",
" <td>0.085126</td>\n",
" <td>0.458646</td>\n",
" <td>0.260199</td>\n",
" <td>0.763087</td>\n",
" <td>0.146362</td>\n",
" <td>0.473122</td>\n",
" <td>0.307269</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>0.000000</td>\n",
" <td>16.000000</td>\n",
" <td>1.520000</td>\n",
" <td>39.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>2.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>0.000000</td>\n",
" <td>19.000000</td>\n",
" <td>1.560000</td>\n",
" <td>42.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>2.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>2.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>0.000000</td>\n",
" <td>20.000000</td>\n",
" <td>1.627689</td>\n",
" <td>45.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>2.000000</td>\n",
" <td>2.000000</td>\n",
" <td>2.000000</td>\n",
" <td>0.000000</td>\n",
" <td>2.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>0.000000</td>\n",
" <td>21.000000</td>\n",
" <td>1.690000</td>\n",
" <td>49.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>2.000000</td>\n",
" <td>2.000000</td>\n",
" <td>2.000000</td>\n",
" <td>0.000000</td>\n",
" <td>3.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>1.000000</td>\n",
" <td>39.000000</td>\n",
" <td>1.720000</td>\n",
" <td>53.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>2.000000</td>\n",
" <td>3.000000</td>\n",
" <td>2.000000</td>\n",
" <td>1.000000</td>\n",
" <td>3.000000</td>\n",
" <td>1.000000</td>\n",
" <td>3.000000</td>\n",
" <td>2.000000</td>\n",
" <td>1.000000</td>\n",
" <td>4.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" jenis_kelamin umur tinggi_badan_meter berat_badan_kilogram \\\n",
"count 138.000000 138.000000 138.000000 138.000000 \n",
"mean 0.130435 20.115942 1.621892 46.065217 \n",
"std 0.338008 3.582342 0.068071 3.765395 \n",
"min 0.000000 16.000000 1.520000 39.000000 \n",
"25% 0.000000 19.000000 1.560000 42.000000 \n",
"50% 0.000000 20.000000 1.627689 45.000000 \n",
"75% 0.000000 21.000000 1.690000 49.000000 \n",
"max 1.000000 39.000000 1.720000 53.000000 \n",
"\n",
" histori_keluarga_kelebihan_BB konsumsi_tinggi_kalori \\\n",
"count 138.000000 138.000000 \n",
"mean 0.224638 0.644928 \n",
"std 0.418864 0.480279 \n",
"min 0.000000 0.000000 \n",
"25% 0.000000 0.000000 \n",
"50% 0.000000 1.000000 \n",
"75% 0.000000 1.000000 \n",
"max 1.000000 1.000000 \n",
"\n",
" konsumsi_sayuran makan_berat ngemil merokok \\\n",
"count 138.000000 138.000000 138.000000 138.000000 \n",
"mean 1.753623 1.891304 1.601449 0.007246 \n",
"std 0.480444 0.751493 0.534091 0.085126 \n",
"min 0.000000 1.000000 0.000000 0.000000 \n",
"25% 2.000000 1.000000 1.000000 0.000000 \n",
"50% 2.000000 2.000000 2.000000 0.000000 \n",
"75% 2.000000 2.000000 2.000000 0.000000 \n",
"max 2.000000 3.000000 2.000000 1.000000 \n",
"\n",
" konsumsi_air_liter pemantauan_kalori aktifitas_fisik \\\n",
"count 138.000000 138.000000 138.000000 \n",
"mean 2.297101 0.072464 0.572464 \n",
"std 0.458646 0.260199 0.763087 \n",
"min 2.000000 0.000000 0.000000 \n",
"25% 2.000000 0.000000 0.000000 \n",
"50% 2.000000 0.000000 0.000000 \n",
"75% 3.000000 0.000000 1.000000 \n",
"max 3.000000 1.000000 3.000000 \n",
"\n",
" penggunaan_perangkat_teknologi konsumsi_alkohol \\\n",
"count 138.000000 138.000000 \n",
"mean 1.021739 0.666667 \n",
"std 0.146362 0.473122 \n",
"min 1.000000 0.000000 \n",
"25% 1.000000 0.000000 \n",
"50% 1.000000 1.000000 \n",
"75% 1.000000 1.000000 \n",
"max 2.000000 1.000000 \n",
"\n",
" transporasi_biasa_digunakan \n",
"count 138.000000 \n",
"mean 1.021739 \n",
"std 0.307269 \n",
"min 0.000000 \n",
"25% 1.000000 \n",
"50% 1.000000 \n",
"75% 1.000000 \n",
"max 4.000000 "
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_pilih_kelas.describe()"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "2ea6072d",
"metadata": {},
"outputs": [],
"source": [
"# excel_file = pd.ExcelWriter(\"smote_training_data_obesitas_hitung.xlsx\")\n",
"# X_trainhitung.to_excel(excel_file)\n",
"# excel_file.save()"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "e65f7d5f",
"metadata": {},
"outputs": [],
"source": [
"# excel_file = pd.ExcelWriter(\"smote_testing_data_obesitas_hitung.xlsx\")\n",
"# X_testhitung.to_excel(excel_file)\n",
"# excel_file.save()"
]
},
{
"cell_type": "markdown",
"id": "e0c29730",
"metadata": {},
"source": [
"## Membagi atribut"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "717762ac",
"metadata": {},
"outputs": [],
"source": [
"X = data.drop(columns='kelas_obesitas', axis = 1)\n",
"Y = data['kelas_obesitas']"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "3bf47956",
"metadata": {},
"outputs": [],
"source": [
"X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size = test_size, stratify = Y, random_state = 0)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "7249aede",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(baris,kolom)\n",
"\n",
"Jumlah data keseluruhan: (705, 16) \n",
"Jumlah data training atau latih: (690, 16) \n",
"Jumlah data test atau uji: (15, 16)\n"
]
}
],
"source": [
"print('(baris,kolom)\\n')\n",
"print('Jumlah data keseluruhan:', X.shape, '\\nJumlah data training atau latih:', X_train.shape, '\\nJumlah data test atau uji:', X_test.shape)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "d91acd11",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"obesitas_I 3\n",
"normal 3\n",
"obesitas_II 3\n",
"berat_badan_kurang 3\n",
"kelebihan_berat_badan 3\n",
"Name: kelas_obesitas, dtype: int64"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Y_test.value_counts()"
]
},
{
"cell_type": "markdown",
"id": "d217a77b",
"metadata": {},
"source": [
"# Normalisasi"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "a2e28cc7",
"metadata": {},
"outputs": [],
"source": [
"minmax = MinMaxScaler()\n",
"minmax.fit(X_train)\n",
"X_train_nomalisasi = minmax.transform(X_train)\n",
"X_test_nomalisasi = minmax.transform(X_test)"
]
},
{
"cell_type": "markdown",
"id": "d149c423",
"metadata": {},
"source": [
"# Model"
]
},
{
"cell_type": "markdown",
"id": "18c55b9a",
"metadata": {},
"source": [
"## naive bayes"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "0a8d5b62",
"metadata": {},
"outputs": [],
"source": [
"klasifikasiNV = GaussianNB()\n",
"start_time_NV = time.time()\n",
"klasifikasiNV.fit(X_train_nomalisasi, Y_train)\n",
"training_end_time_NV = time.time()\n",
"Y_predictNV = klasifikasiNV.predict(X_test_nomalisasi)\n",
"end_time_NV = time.time()\n",
"prediction_end_time_NV = time.time()"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "ec0a6b15",
"metadata": {},
"outputs": [],
"source": [
"training_execution_time_NV = training_end_time_NV - start_time_NV\n",
"prediction_execution_time_NV = prediction_end_time_NV - training_end_time_NV\n",
"execution_time_NV1 = prediction_end_time_NV - start_time_NV\n",
"execution_time_NV2 = end_time_NV - start_time_NV"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "f26dc8fd",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Waktu awal eksekusi Naive Bayes: 1717540795.9984713 detik\n",
"Waktu akhir eksekusi Naive Bayes: 1717540796.0061162 detik\n",
"Waktu pelatihan Naive Bayes: 0.00538182258605957 detik\n",
"Waktu uji Naive Bayes: 0.0022630691528320312 detik\n",
"Total waktu eksekusi Naive Bayes: 0.0076448917388916016 detik\n",
"Total waktu eksekusi Naive Bayes: 0.0076448917388916016 detik\n"
]
}
],
"source": [
"print(f\"Waktu awal eksekusi Naive Bayes: {start_time_NV} detik\")\n",
"print(f\"Waktu akhir eksekusi Naive Bayes: {end_time_NV} detik\")\n",
"print(f\"Waktu pelatihan Naive Bayes: {training_execution_time_NV} detik\")\n",
"print(f\"Waktu uji Naive Bayes: {prediction_execution_time_NV} detik\")\n",
"print(f\"Total waktu eksekusi Naive Bayes: {execution_time_NV1} detik\")\n",
"print(f\"Total waktu eksekusi Naive Bayes: {execution_time_NV2} detik\")"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "a262d7b6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" berat_badan_kurang 0.75 1.00 0.86 3\n",
"kelebihan_berat_badan 0.50 0.33 0.40 3\n",
" normal 0.50 0.33 0.40 3\n",
" obesitas_I 1.00 0.33 0.50 3\n",
" obesitas_II 0.50 1.00 0.67 3\n",
"\n",
" accuracy 0.60 15\n",
" macro avg 0.65 0.60 0.56 15\n",
" weighted avg 0.65 0.60 0.56 15\n",
"\n"
]
}
],
"source": [
"evaluasiNV = classification_report(Y_test, Y_predictNV)\n",
"print(evaluasiNV)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "b187e3f0",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>berat_badan_kurang</th>\n",
" <th>normal</th>\n",
" <th>kelebihan_berat_badan</th>\n",
" <th>obesitas_I</th>\n",
" <th>obesitas_II</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>berat_badan_kurang</th>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>normal</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>kelebihan_berat_badan</th>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>obesitas_I</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>obesitas_II</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" berat_badan_kurang normal kelebihan_berat_badan \\\n",
"berat_badan_kurang 3 0 0 \n",
"normal 1 1 1 \n",
"kelebihan_berat_badan 0 1 1 \n",
"obesitas_I 0 0 0 \n",
"obesitas_II 0 0 0 \n",
"\n",
" obesitas_I obesitas_II \n",
"berat_badan_kurang 0 0 \n",
"normal 0 0 \n",
"kelebihan_berat_badan 0 1 \n",
"obesitas_I 1 2 \n",
"obesitas_II 0 3 "
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"label_unikNV = np.unique(np.concatenate((Y_test, Y_predictNV)))\n",
"\n",
"# Membuat matriks kebingungan dengan label\n",
"matrixNV = confusion_matrix(Y_test, Y_predictNV, labels=label_unikNV)\n",
"\n",
"# Membuat DataFrame dari matriks kebingungan\n",
"dataframe_CM_NV = pd.DataFrame(matrixNV, index=label_unikNV, columns=label_unikNV)\n",
"\n",
"# Mengatur urutan baru\n",
"urutan_baru = ['berat_badan_kurang', 'normal', 'kelebihan_berat_badan', 'obesitas_I', 'obesitas_II']\n",
"\n",
"# Menyusun ulang matriks dan DataFrame sesuai urutan baru\n",
"matrixNV_baru = dataframe_CM_NV.reindex(index=urutan_baru, columns=urutan_baru)\n",
"matrixNV_baru"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "16c10f86",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 800x600 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set(font_scale=1)\n",
"plt.figure(figsize=(8, 6))\n",
"heatmap = sns.heatmap(matrixNV_baru, annot=True, fmt=\"d\", cmap=\"Greens\", xticklabels=urutan_baru, yticklabels=urutan_baru)\n",
"heatmap.set_xlabel(\"Predicted Label\")\n",
"heatmap.set_ylabel(\"True Label\")\n",
"plt.xticks(rotation=20, ha='right')\n",
"heatmap.set_title(\"Confusion Matrix Heatmap\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "61576256",
"metadata": {},
"source": [
"## KNN"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "5a7945b4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"nilai K: 3 , memiliki akurasi 0.7814285714285714\n",
"nilai K: 4 , memiliki akurasi 0.85\n",
"nilai K: 5 , memiliki akurasi 0.85\n",
"nilai K: 6 , memiliki akurasi 0.9314285714285715\n",
"nilai K: 7 , memiliki akurasi 1.0\n",
"nilai K: 8 , memiliki akurasi 0.85\n",
"nilai K: 9 , memiliki akurasi 1.0\n",
"nilai K: 10 , memiliki akurasi 1.0\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1200x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"k_values = []\n",
"accuracy_values = []\n",
"precision_values = []\n",
"recall_values = []\n",
"f1_score_values = []\n",
"sns.set_style(\"whitegrid\")\n",
"for k in range(3,11):\n",
" klasifikasiKNN = KNeighborsClassifier(n_neighbors = k)\n",
" klasifikasiKNN.fit(X_train_nomalisasi, Y_train)\n",
" Y_predictKNN = klasifikasiKNN.predict(X_test_nomalisasi)\n",
" akurasi = accuracy_score(Y_test, Y_predictKNN)\n",
" presisi = precision_score(Y_test, Y_predictKNN, average='macro')\n",
" recal = recall_score(Y_test, Y_predictKNN, average='macro')\n",
" F1 = f1_score(Y_test, Y_predictKNN, average='macro')\n",
" k =+ k\n",
" k_values.append(k)\n",
" accuracy_values.append(akurasi)\n",
" precision_values.append(presisi)\n",
" recall_values.append(recal)\n",
" f1_score_values.append(F1)\n",
" print('nilai K:',k, ', memiliki akurasi', F1)\n",
" \n",
"plt.figure(figsize=(12, 6))\n",
"plt.plot(k_values, accuracy_values, marker='o', markersize=4, linestyle='-', color='#E81416', label='Akurasi')\n",
"plt.plot(k_values, precision_values, marker='o', markersize=4, linestyle='-', color='#FFA500', label='Presisi')\n",
"plt.plot(k_values, recall_values, marker='o', markersize=4, linestyle='-', color='#FAEB36', label='Recal')\n",
"plt.plot(k_values, f1_score_values, marker='o', markersize=4, linestyle='-', color='#79C314', label='Skor F1')\n",
"\n",
"plt.title('Hasil Kinerja K-Nearest Neighbor terhadap Nilai K untuk Rasio Data 690:15')\n",
"plt.xlabel('Nilai K')\n",
"plt.ylabel('Nilai Kinerja')\n",
"plt.xticks(k_values)\n",
"plt.grid(True, alpha=0.4)\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "ac8fa753",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"nilai K: 3 , memiliki train 0.004224300384521484\n",
"nilai K: 3 , memiliki test 0.009124279022216797\n",
"nilai K: 4 , memiliki train 0.005000591278076172\n",
"nilai K: 4 , memiliki test 0.009795427322387695\n",
"nilai K: 5 , memiliki train 0.00208282470703125\n",
"nilai K: 5 , memiliki test 0.011575698852539062\n",
"nilai K: 6 , memiliki train 0.0027952194213867188\n",
"nilai K: 6 , memiliki test 0.011479854583740234\n",
"nilai K: 7 , memiliki train 0.002368927001953125\n",
"nilai K: 7 , memiliki test 0.010772466659545898\n",
"nilai K: 8 , memiliki train 0.0022971630096435547\n",
"nilai K: 8 , memiliki test 0.008573293685913086\n",
"nilai K: 9 , memiliki train 0.0019996166229248047\n",
"nilai K: 9 , memiliki test 0.007220029830932617\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1200x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"k_values = []\n",
"train_values = []\n",
"test_values = []\n",
"\n",
"sns.set_style(\"whitegrid\")\n",
"\n",
"for k in range(3,10):\n",
" klasifikasiKNN = KNeighborsClassifier(n_neighbors = k)\n",
" start_time_KNN = time.time()\n",
" klasifikasiKNN.fit(X_train_nomalisasi, Y_train)\n",
" training_end_time_KNN = time.time()\n",
" Y_predictKNN = klasifikasiKNN.predict(X_test_nomalisasi)\n",
" prediction_end_time_KNN = time.time()\n",
"\n",
" train = training_end_time_KNN - start_time_KNN\n",
" test = prediction_end_time_KNN - training_end_time_KNN\n",
" \n",
" k =+ k\n",
" k_values.append(k)\n",
" train_values.append(train)\n",
" test_values.append(test)\n",
" print('nilai K:',k, ', memiliki train', train)\n",
" print('nilai K:',k, ', memiliki test', test)\n",
" \n",
"plt.figure(figsize=(12, 6))\n",
"plt.plot(k_values, train_values, marker='o', markersize=4, linestyle='-', color='#487DE7', label='Waktu Pelatihan')\n",
"plt.plot(k_values, test_values, marker='o', markersize=4, linestyle='-', color='#70369D', label='Waktu Pengujian')\n",
"\n",
"\n",
"plt.title('Hasil Kinerja K-Nearest Neighbor terhadap Nilai K')\n",
"plt.xlabel('Nilai K')\n",
"plt.ylabel('Waktu')\n",
"plt.xticks(k_values)\n",
"plt.grid(True, alpha=0.4)\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "4bb61323",
"metadata": {},
"outputs": [],
"source": [
"klasifikasiKNN = KNeighborsClassifier(n_neighbors = 7)\n",
"start_time_KNN = time.time()\n",
"klasifikasiKNN.fit(X_train_nomalisasi, Y_train)\n",
"training_end_time_KNN = time.time()\n",
"Y_predictKNN = klasifikasiKNN.predict(X_test_nomalisasi)\n",
"end_time_KNN = time.time()\n",
"prediction_end_time_KNN = time.time()"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "aeaf9149",
"metadata": {},
"outputs": [],
"source": [
"training_execution_time_KNN = training_end_time_KNN - start_time_KNN\n",
"prediction_execution_time_KNN = prediction_end_time_KNN - training_end_time_KNN\n",
"execution_time_KNN1 = prediction_end_time_KNN - start_time_KNN\n",
"execution_time_KNN2 = end_time_KNN - start_time_KNN"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "b23d1b1e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Waktu awal eksekusi KNN: 1717540798.019642 detik\n",
"Waktu akhir eksekusi KNN: 1717540798.0392237 detik\n",
"Waktu pelatihan KNN: 0.004997968673706055 detik\n",
"Waktu uji KNN: 0.014583587646484375 detik\n",
"Total waktu eksekusi KNN: 0.01958155632019043 detik\n",
"Total waktu eksekusi KNN: 0.01958155632019043 detik\n"
]
}
],
"source": [
"print(f\"Waktu awal eksekusi KNN: {start_time_KNN} detik\")\n",
"print(f\"Waktu akhir eksekusi KNN: {end_time_KNN} detik\")\n",
"print(f\"Waktu pelatihan KNN: {training_execution_time_KNN} detik\")\n",
"print(f\"Waktu uji KNN: {prediction_execution_time_KNN} detik\")\n",
"print(f\"Total waktu eksekusi KNN: {execution_time_KNN1} detik\")\n",
"print(f\"Total waktu eksekusi KNN: {execution_time_KNN2} detik\")"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "1353c77e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" precision recall f1-score support\n",
"\n",
" berat_badan_kurang 1.00 1.00 1.00 3\n",
"kelebihan_berat_badan 1.00 1.00 1.00 3\n",
" normal 1.00 1.00 1.00 3\n",
" obesitas_I 1.00 1.00 1.00 3\n",
" obesitas_II 1.00 1.00 1.00 3\n",
"\n",
" accuracy 1.00 15\n",
" macro avg 1.00 1.00 1.00 15\n",
" weighted avg 1.00 1.00 1.00 15\n",
"\n"
]
}
],
"source": [
"evaluasiKNN = classification_report(Y_test, Y_predictKNN)\n",
"print(evaluasiKNN)"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "abdc93b9",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>berat_badan_kurang</th>\n",
" <th>normal</th>\n",
" <th>kelebihan_berat_badan</th>\n",
" <th>obesitas_I</th>\n",
" <th>obesitas_II</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>berat_badan_kurang</th>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>normal</th>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>kelebihan_berat_badan</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>obesitas_I</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>obesitas_II</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" berat_badan_kurang normal kelebihan_berat_badan \\\n",
"berat_badan_kurang 3 0 0 \n",
"normal 0 3 0 \n",
"kelebihan_berat_badan 0 0 3 \n",
"obesitas_I 0 0 0 \n",
"obesitas_II 0 0 0 \n",
"\n",
" obesitas_I obesitas_II \n",
"berat_badan_kurang 0 0 \n",
"normal 0 0 \n",
"kelebihan_berat_badan 0 0 \n",
"obesitas_I 3 0 \n",
"obesitas_II 0 3 "
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"label_unikKNN = np.unique(np.concatenate((Y_test, Y_predictKNN)))\n",
"\n",
"# Membuat matriks kebingungan dengan label\n",
"matrixKNN = confusion_matrix(Y_test, Y_predictKNN, labels=label_unikKNN)\n",
"\n",
"# Membuat DataFrame dari matriks kebingungan\n",
"dataframe_CM_KNN = pd.DataFrame(matrixKNN, index=label_unikKNN, columns=label_unikKNN)\n",
"\n",
"# Menyusun ulang matriks dan DataFrame sesuai urutan baru\n",
"matrixKNN_baru = dataframe_CM_KNN.reindex(index=urutan_baru, columns=urutan_baru)\n",
"matrixKNN_baru"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "c72c9b04",
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 800x600 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set(font_scale=1)\n",
"plt.figure(figsize=(8, 6))\n",
"heatmap = sns.heatmap(matrixKNN_baru, annot=True, fmt=\"d\", cmap=\"Blues\", xticklabels=urutan_baru, yticklabels=urutan_baru)\n",
"heatmap.set_xlabel(\"Predicted Label\")\n",
"heatmap.set_ylabel(\"True Label\")\n",
"plt.xticks(rotation=20, ha='right')\n",
"heatmap.set_title(\"Confusion Matrix Heatmap\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "d417353b",
"metadata": {},
"source": [
"## Data hasil klasifikasi dari naive bayes dan knn"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "58c9135d",
"metadata": {},
"outputs": [],
"source": [
"dataNV = X_testbaru.copy()\n",
"dataKNN = X_testbaru.copy()\n",
"data_NV_KNN = X_testbaru.copy()"
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "fdf4e4a3",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>jenis_kelamin</th>\n",
" <th>umur</th>\n",
" <th>tinggi_badan_meter</th>\n",
" <th>berat_badan_kilogram</th>\n",
" <th>histori_keluarga_kelebihan_BB</th>\n",
" <th>konsumsi_tinggi_kalori</th>\n",
" <th>konsumsi_sayuran</th>\n",
" <th>makan_berat</th>\n",
" <th>ngemil</th>\n",
" <th>merokok</th>\n",
" <th>konsumsi_air_liter</th>\n",
" <th>pemantauan_kalori</th>\n",
" <th>aktifitas_fisik</th>\n",
" <th>penggunaan_perangkat_teknologi</th>\n",
" <th>konsumsi_alkohol</th>\n",
" <th>transporasi_biasa_digunakan</th>\n",
" <th>kelas_obesitas</th>\n",
" <th>klasifikasi_naive_bayes</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>606</th>\n",
" <td>Perempuan</td>\n",
" <td>31</td>\n",
" <td>1.672625</td>\n",
" <td>71</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_I</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>71</th>\n",
" <td>Perempuan</td>\n",
" <td>19</td>\n",
" <td>1.650000</td>\n",
" <td>56</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Sering</td>\n",
" <td>Ya</td>\n",
" <td>Lebih 2 liter</td>\n",
" <td>Ya</td>\n",
" <td>1-2 hari</td>\n",
" <td>3-5 jam</td>\n",
" <td>Sering</td>\n",
" <td>Sepeda motor</td>\n",
" <td>normal</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>609</th>\n",
" <td>Perempuan</td>\n",
" <td>39</td>\n",
" <td>1.711621</td>\n",
" <td>84</td>\n",
" <td>Tidak</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>Lebih 2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_I</td>\n",
" <td>obesitas_I</td>\n",
" </tr>\n",
" <tr>\n",
" <th>678</th>\n",
" <td>Perempuan</td>\n",
" <td>37</td>\n",
" <td>1.560000</td>\n",
" <td>79</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>644</th>\n",
" <td>Perempuan</td>\n",
" <td>39</td>\n",
" <td>1.528746</td>\n",
" <td>79</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>275</th>\n",
" <td>Perempuan</td>\n",
" <td>20</td>\n",
" <td>1.550000</td>\n",
" <td>41</td>\n",
" <td>Tidak</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Sering</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>berat_badan_kurang</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>173</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.540000</td>\n",
" <td>47</td>\n",
" <td>Ya</td>\n",
" <td>Tidak</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Selalu</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>2-4 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>normal</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>510</th>\n",
" <td>Perempuan</td>\n",
" <td>25</td>\n",
" <td>1.643548</td>\n",
" <td>62</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Mobil</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>548</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.641347</td>\n",
" <td>66</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>389</th>\n",
" <td>Laki-laki</td>\n",
" <td>39</td>\n",
" <td>1.720000</td>\n",
" <td>86</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_I</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>394</th>\n",
" <td>Perempuan</td>\n",
" <td>37</td>\n",
" <td>1.560000</td>\n",
" <td>77</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>206</th>\n",
" <td>Perempuan</td>\n",
" <td>18</td>\n",
" <td>1.640000</td>\n",
" <td>59</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>normal</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>295</th>\n",
" <td>Perempuan</td>\n",
" <td>19</td>\n",
" <td>1.680000</td>\n",
" <td>49</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>berat_badan_kurang</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>480</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.694749</td>\n",
" <td>49</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Sering</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>berat_badan_kurang</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>124</th>\n",
" <td>Perempuan</td>\n",
" <td>20</td>\n",
" <td>1.630000</td>\n",
" <td>64</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Tidak pernah</td>\n",
" <td>3x</td>\n",
" <td>Selalu</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>3-5 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Jalan kaki</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" jenis_kelamin umur tinggi_badan_meter berat_badan_kilogram \\\n",
"606 Perempuan 31 1.672625 71 \n",
"71 Perempuan 19 1.650000 56 \n",
"609 Perempuan 39 1.711621 84 \n",
"678 Perempuan 37 1.560000 79 \n",
"644 Perempuan 39 1.528746 79 \n",
"275 Perempuan 20 1.550000 41 \n",
"173 Perempuan 21 1.540000 47 \n",
"510 Perempuan 25 1.643548 62 \n",
"548 Perempuan 21 1.641347 66 \n",
"389 Laki-laki 39 1.720000 86 \n",
"394 Perempuan 37 1.560000 77 \n",
"206 Perempuan 18 1.640000 59 \n",
"295 Perempuan 19 1.680000 49 \n",
"480 Perempuan 21 1.694749 49 \n",
"124 Perempuan 20 1.630000 64 \n",
"\n",
" histori_keluarga_kelebihan_BB konsumsi_tinggi_kalori konsumsi_sayuran \\\n",
"606 Ya Ya Kadang-kadang \n",
"71 Ya Ya Selalu \n",
"609 Tidak Ya Selalu \n",
"678 Ya Ya Kadang-kadang \n",
"644 Ya Ya Kadang-kadang \n",
"275 Tidak Ya Selalu \n",
"173 Ya Tidak Selalu \n",
"510 Tidak Tidak Kadang-kadang \n",
"548 Ya Ya Selalu \n",
"389 Ya Ya Selalu \n",
"394 Ya Ya Kadang-kadang \n",
"206 Ya Ya Kadang-kadang \n",
"295 Tidak Tidak Selalu \n",
"480 Ya Ya Selalu \n",
"124 Ya Ya Tidak pernah \n",
"\n",
" makan_berat ngemil merokok konsumsi_air_liter pemantauan_kalori \\\n",
"606 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"71 3x Sering Ya Lebih 2 liter Ya \n",
"609 1-2x Kadang-kadang Tidak Lebih 2 liter Tidak \n",
"678 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"644 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"275 1-2x Sering Tidak 1-2 liter Tidak \n",
"173 3x Selalu Tidak 1-2 liter Tidak \n",
"510 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"548 1-2x Kadang-kadang Tidak 1-2 liter Tidak \n",
"389 1-2x Kadang-kadang Tidak 1-2 liter Tidak \n",
"394 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"206 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"295 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"480 3x Sering Tidak 1-2 liter Tidak \n",
"124 3x Selalu Tidak 1-2 liter Tidak \n",
"\n",
" aktifitas_fisik penggunaan_perangkat_teknologi konsumsi_alkohol \\\n",
"606 Tidak pernah 0-2 jam Kadang-kadang \n",
"71 1-2 hari 3-5 jam Sering \n",
"609 Tidak pernah 0-2 jam Tidak pernah \n",
"678 Tidak pernah 0-2 jam Kadang-kadang \n",
"644 Tidak pernah 0-2 jam Kadang-kadang \n",
"275 Tidak pernah 0-2 jam Kadang-kadang \n",
"173 2-4 hari 0-2 jam Tidak pernah \n",
"510 1-2 hari 0-2 jam Tidak pernah \n",
"548 Tidak pernah 0-2 jam Tidak pernah \n",
"389 Tidak pernah 0-2 jam Tidak pernah \n",
"394 Tidak pernah 0-2 jam Kadang-kadang \n",
"206 1-2 hari 0-2 jam Kadang-kadang \n",
"295 1-2 hari 0-2 jam Kadang-kadang \n",
"480 Tidak pernah 0-2 jam Tidak pernah \n",
"124 Tidak pernah 3-5 jam Tidak pernah \n",
"\n",
" transporasi_biasa_digunakan kelas_obesitas klasifikasi_naive_bayes \n",
"606 Jalan kaki obesitas_I obesitas_II \n",
"71 Sepeda motor normal normal \n",
"609 Jalan kaki obesitas_I obesitas_I \n",
"678 Jalan kaki obesitas_II obesitas_II \n",
"644 Jalan kaki obesitas_II obesitas_II \n",
"275 Sepeda motor berat_badan_kurang berat_badan_kurang \n",
"173 Sepeda motor normal berat_badan_kurang \n",
"510 Mobil kelebihan_berat_badan kelebihan_berat_badan \n",
"548 Sepeda motor kelebihan_berat_badan obesitas_II \n",
"389 Jalan kaki obesitas_I obesitas_II \n",
"394 Jalan kaki obesitas_II obesitas_II \n",
"206 Sepeda motor normal kelebihan_berat_badan \n",
"295 Sepeda motor berat_badan_kurang berat_badan_kurang \n",
"480 Sepeda motor berat_badan_kurang berat_badan_kurang \n",
"124 Jalan kaki kelebihan_berat_badan normal "
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataNV['klasifikasi_naive_bayes'] = Y_predictNV\n",
"dataNV"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "c37a4704",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
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" .dataframe thead th {\n",
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>jenis_kelamin</th>\n",
" <th>umur</th>\n",
" <th>tinggi_badan_meter</th>\n",
" <th>berat_badan_kilogram</th>\n",
" <th>histori_keluarga_kelebihan_BB</th>\n",
" <th>konsumsi_tinggi_kalori</th>\n",
" <th>konsumsi_sayuran</th>\n",
" <th>makan_berat</th>\n",
" <th>ngemil</th>\n",
" <th>merokok</th>\n",
" <th>konsumsi_air_liter</th>\n",
" <th>pemantauan_kalori</th>\n",
" <th>aktifitas_fisik</th>\n",
" <th>penggunaan_perangkat_teknologi</th>\n",
" <th>konsumsi_alkohol</th>\n",
" <th>transporasi_biasa_digunakan</th>\n",
" <th>kelas_obesitas</th>\n",
" <th>klasifikasi_k_nearest_neighbor</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>606</th>\n",
" <td>Perempuan</td>\n",
" <td>31</td>\n",
" <td>1.672625</td>\n",
" <td>71</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_I</td>\n",
" <td>obesitas_I</td>\n",
" </tr>\n",
" <tr>\n",
" <th>71</th>\n",
" <td>Perempuan</td>\n",
" <td>19</td>\n",
" <td>1.650000</td>\n",
" <td>56</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Sering</td>\n",
" <td>Ya</td>\n",
" <td>Lebih 2 liter</td>\n",
" <td>Ya</td>\n",
" <td>1-2 hari</td>\n",
" <td>3-5 jam</td>\n",
" <td>Sering</td>\n",
" <td>Sepeda motor</td>\n",
" <td>normal</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>609</th>\n",
" <td>Perempuan</td>\n",
" <td>39</td>\n",
" <td>1.711621</td>\n",
" <td>84</td>\n",
" <td>Tidak</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>Lebih 2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_I</td>\n",
" <td>obesitas_I</td>\n",
" </tr>\n",
" <tr>\n",
" <th>678</th>\n",
" <td>Perempuan</td>\n",
" <td>37</td>\n",
" <td>1.560000</td>\n",
" <td>79</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>644</th>\n",
" <td>Perempuan</td>\n",
" <td>39</td>\n",
" <td>1.528746</td>\n",
" <td>79</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>275</th>\n",
" <td>Perempuan</td>\n",
" <td>20</td>\n",
" <td>1.550000</td>\n",
" <td>41</td>\n",
" <td>Tidak</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Sering</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>berat_badan_kurang</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>173</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.540000</td>\n",
" <td>47</td>\n",
" <td>Ya</td>\n",
" <td>Tidak</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Selalu</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>2-4 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>normal</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>510</th>\n",
" <td>Perempuan</td>\n",
" <td>25</td>\n",
" <td>1.643548</td>\n",
" <td>62</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Mobil</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>548</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.641347</td>\n",
" <td>66</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>389</th>\n",
" <td>Laki-laki</td>\n",
" <td>39</td>\n",
" <td>1.720000</td>\n",
" <td>86</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_I</td>\n",
" <td>obesitas_I</td>\n",
" </tr>\n",
" <tr>\n",
" <th>394</th>\n",
" <td>Perempuan</td>\n",
" <td>37</td>\n",
" <td>1.560000</td>\n",
" <td>77</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>206</th>\n",
" <td>Perempuan</td>\n",
" <td>18</td>\n",
" <td>1.640000</td>\n",
" <td>59</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>normal</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>295</th>\n",
" <td>Perempuan</td>\n",
" <td>19</td>\n",
" <td>1.680000</td>\n",
" <td>49</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>berat_badan_kurang</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>480</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.694749</td>\n",
" <td>49</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Sering</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>berat_badan_kurang</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>124</th>\n",
" <td>Perempuan</td>\n",
" <td>20</td>\n",
" <td>1.630000</td>\n",
" <td>64</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Tidak pernah</td>\n",
" <td>3x</td>\n",
" <td>Selalu</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>3-5 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Jalan kaki</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" jenis_kelamin umur tinggi_badan_meter berat_badan_kilogram \\\n",
"606 Perempuan 31 1.672625 71 \n",
"71 Perempuan 19 1.650000 56 \n",
"609 Perempuan 39 1.711621 84 \n",
"678 Perempuan 37 1.560000 79 \n",
"644 Perempuan 39 1.528746 79 \n",
"275 Perempuan 20 1.550000 41 \n",
"173 Perempuan 21 1.540000 47 \n",
"510 Perempuan 25 1.643548 62 \n",
"548 Perempuan 21 1.641347 66 \n",
"389 Laki-laki 39 1.720000 86 \n",
"394 Perempuan 37 1.560000 77 \n",
"206 Perempuan 18 1.640000 59 \n",
"295 Perempuan 19 1.680000 49 \n",
"480 Perempuan 21 1.694749 49 \n",
"124 Perempuan 20 1.630000 64 \n",
"\n",
" histori_keluarga_kelebihan_BB konsumsi_tinggi_kalori konsumsi_sayuran \\\n",
"606 Ya Ya Kadang-kadang \n",
"71 Ya Ya Selalu \n",
"609 Tidak Ya Selalu \n",
"678 Ya Ya Kadang-kadang \n",
"644 Ya Ya Kadang-kadang \n",
"275 Tidak Ya Selalu \n",
"173 Ya Tidak Selalu \n",
"510 Tidak Tidak Kadang-kadang \n",
"548 Ya Ya Selalu \n",
"389 Ya Ya Selalu \n",
"394 Ya Ya Kadang-kadang \n",
"206 Ya Ya Kadang-kadang \n",
"295 Tidak Tidak Selalu \n",
"480 Ya Ya Selalu \n",
"124 Ya Ya Tidak pernah \n",
"\n",
" makan_berat ngemil merokok konsumsi_air_liter pemantauan_kalori \\\n",
"606 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"71 3x Sering Ya Lebih 2 liter Ya \n",
"609 1-2x Kadang-kadang Tidak Lebih 2 liter Tidak \n",
"678 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"644 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"275 1-2x Sering Tidak 1-2 liter Tidak \n",
"173 3x Selalu Tidak 1-2 liter Tidak \n",
"510 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"548 1-2x Kadang-kadang Tidak 1-2 liter Tidak \n",
"389 1-2x Kadang-kadang Tidak 1-2 liter Tidak \n",
"394 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"206 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"295 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"480 3x Sering Tidak 1-2 liter Tidak \n",
"124 3x Selalu Tidak 1-2 liter Tidak \n",
"\n",
" aktifitas_fisik penggunaan_perangkat_teknologi konsumsi_alkohol \\\n",
"606 Tidak pernah 0-2 jam Kadang-kadang \n",
"71 1-2 hari 3-5 jam Sering \n",
"609 Tidak pernah 0-2 jam Tidak pernah \n",
"678 Tidak pernah 0-2 jam Kadang-kadang \n",
"644 Tidak pernah 0-2 jam Kadang-kadang \n",
"275 Tidak pernah 0-2 jam Kadang-kadang \n",
"173 2-4 hari 0-2 jam Tidak pernah \n",
"510 1-2 hari 0-2 jam Tidak pernah \n",
"548 Tidak pernah 0-2 jam Tidak pernah \n",
"389 Tidak pernah 0-2 jam Tidak pernah \n",
"394 Tidak pernah 0-2 jam Kadang-kadang \n",
"206 1-2 hari 0-2 jam Kadang-kadang \n",
"295 1-2 hari 0-2 jam Kadang-kadang \n",
"480 Tidak pernah 0-2 jam Tidak pernah \n",
"124 Tidak pernah 3-5 jam Tidak pernah \n",
"\n",
" transporasi_biasa_digunakan kelas_obesitas \\\n",
"606 Jalan kaki obesitas_I \n",
"71 Sepeda motor normal \n",
"609 Jalan kaki obesitas_I \n",
"678 Jalan kaki obesitas_II \n",
"644 Jalan kaki obesitas_II \n",
"275 Sepeda motor berat_badan_kurang \n",
"173 Sepeda motor normal \n",
"510 Mobil kelebihan_berat_badan \n",
"548 Sepeda motor kelebihan_berat_badan \n",
"389 Jalan kaki obesitas_I \n",
"394 Jalan kaki obesitas_II \n",
"206 Sepeda motor normal \n",
"295 Sepeda motor berat_badan_kurang \n",
"480 Sepeda motor berat_badan_kurang \n",
"124 Jalan kaki kelebihan_berat_badan \n",
"\n",
" klasifikasi_k_nearest_neighbor \n",
"606 obesitas_I \n",
"71 normal \n",
"609 obesitas_I \n",
"678 obesitas_II \n",
"644 obesitas_II \n",
"275 berat_badan_kurang \n",
"173 normal \n",
"510 kelebihan_berat_badan \n",
"548 kelebihan_berat_badan \n",
"389 obesitas_I \n",
"394 obesitas_II \n",
"206 normal \n",
"295 berat_badan_kurang \n",
"480 berat_badan_kurang \n",
"124 kelebihan_berat_badan "
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataKNN['klasifikasi_k_nearest_neighbor'] = Y_predictKNN\n",
"dataKNN"
]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "0c8ed05b",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>jenis_kelamin</th>\n",
" <th>umur</th>\n",
" <th>tinggi_badan_meter</th>\n",
" <th>berat_badan_kilogram</th>\n",
" <th>histori_keluarga_kelebihan_BB</th>\n",
" <th>konsumsi_tinggi_kalori</th>\n",
" <th>konsumsi_sayuran</th>\n",
" <th>makan_berat</th>\n",
" <th>ngemil</th>\n",
" <th>merokok</th>\n",
" <th>konsumsi_air_liter</th>\n",
" <th>pemantauan_kalori</th>\n",
" <th>aktifitas_fisik</th>\n",
" <th>penggunaan_perangkat_teknologi</th>\n",
" <th>konsumsi_alkohol</th>\n",
" <th>transporasi_biasa_digunakan</th>\n",
" <th>kelas_obesitas</th>\n",
" <th>klasifikasi_naive_bayes</th>\n",
" <th>klasifikasi_k_nearest_neighbor</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>606</th>\n",
" <td>Perempuan</td>\n",
" <td>31</td>\n",
" <td>1.672625</td>\n",
" <td>71</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_I</td>\n",
" <td>obesitas_II</td>\n",
" <td>obesitas_I</td>\n",
" </tr>\n",
" <tr>\n",
" <th>71</th>\n",
" <td>Perempuan</td>\n",
" <td>19</td>\n",
" <td>1.650000</td>\n",
" <td>56</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Sering</td>\n",
" <td>Ya</td>\n",
" <td>Lebih 2 liter</td>\n",
" <td>Ya</td>\n",
" <td>1-2 hari</td>\n",
" <td>3-5 jam</td>\n",
" <td>Sering</td>\n",
" <td>Sepeda motor</td>\n",
" <td>normal</td>\n",
" <td>normal</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>609</th>\n",
" <td>Perempuan</td>\n",
" <td>39</td>\n",
" <td>1.711621</td>\n",
" <td>84</td>\n",
" <td>Tidak</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>Lebih 2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_I</td>\n",
" <td>obesitas_I</td>\n",
" <td>obesitas_I</td>\n",
" </tr>\n",
" <tr>\n",
" <th>678</th>\n",
" <td>Perempuan</td>\n",
" <td>37</td>\n",
" <td>1.560000</td>\n",
" <td>79</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" <td>obesitas_II</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>644</th>\n",
" <td>Perempuan</td>\n",
" <td>39</td>\n",
" <td>1.528746</td>\n",
" <td>79</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" <td>obesitas_II</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>275</th>\n",
" <td>Perempuan</td>\n",
" <td>20</td>\n",
" <td>1.550000</td>\n",
" <td>41</td>\n",
" <td>Tidak</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Sering</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>berat_badan_kurang</td>\n",
" <td>berat_badan_kurang</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>173</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.540000</td>\n",
" <td>47</td>\n",
" <td>Ya</td>\n",
" <td>Tidak</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Selalu</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>2-4 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>normal</td>\n",
" <td>berat_badan_kurang</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>510</th>\n",
" <td>Perempuan</td>\n",
" <td>25</td>\n",
" <td>1.643548</td>\n",
" <td>62</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Mobil</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>548</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.641347</td>\n",
" <td>66</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>obesitas_II</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>389</th>\n",
" <td>Laki-laki</td>\n",
" <td>39</td>\n",
" <td>1.720000</td>\n",
" <td>86</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>1-2x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_I</td>\n",
" <td>obesitas_II</td>\n",
" <td>obesitas_I</td>\n",
" </tr>\n",
" <tr>\n",
" <th>394</th>\n",
" <td>Perempuan</td>\n",
" <td>37</td>\n",
" <td>1.560000</td>\n",
" <td>77</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Jalan kaki</td>\n",
" <td>obesitas_II</td>\n",
" <td>obesitas_II</td>\n",
" <td>obesitas_II</td>\n",
" </tr>\n",
" <tr>\n",
" <th>206</th>\n",
" <td>Perempuan</td>\n",
" <td>18</td>\n",
" <td>1.640000</td>\n",
" <td>59</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>normal</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>normal</td>\n",
" </tr>\n",
" <tr>\n",
" <th>295</th>\n",
" <td>Perempuan</td>\n",
" <td>19</td>\n",
" <td>1.680000</td>\n",
" <td>49</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 hari</td>\n",
" <td>0-2 jam</td>\n",
" <td>Kadang-kadang</td>\n",
" <td>Sepeda motor</td>\n",
" <td>berat_badan_kurang</td>\n",
" <td>berat_badan_kurang</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>480</th>\n",
" <td>Perempuan</td>\n",
" <td>21</td>\n",
" <td>1.694749</td>\n",
" <td>49</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Selalu</td>\n",
" <td>3x</td>\n",
" <td>Sering</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>0-2 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Sepeda motor</td>\n",
" <td>berat_badan_kurang</td>\n",
" <td>berat_badan_kurang</td>\n",
" <td>berat_badan_kurang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>124</th>\n",
" <td>Perempuan</td>\n",
" <td>20</td>\n",
" <td>1.630000</td>\n",
" <td>64</td>\n",
" <td>Ya</td>\n",
" <td>Ya</td>\n",
" <td>Tidak pernah</td>\n",
" <td>3x</td>\n",
" <td>Selalu</td>\n",
" <td>Tidak</td>\n",
" <td>1-2 liter</td>\n",
" <td>Tidak</td>\n",
" <td>Tidak pernah</td>\n",
" <td>3-5 jam</td>\n",
" <td>Tidak pernah</td>\n",
" <td>Jalan kaki</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>normal</td>\n",
" <td>kelebihan_berat_badan</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" jenis_kelamin umur tinggi_badan_meter berat_badan_kilogram \\\n",
"606 Perempuan 31 1.672625 71 \n",
"71 Perempuan 19 1.650000 56 \n",
"609 Perempuan 39 1.711621 84 \n",
"678 Perempuan 37 1.560000 79 \n",
"644 Perempuan 39 1.528746 79 \n",
"275 Perempuan 20 1.550000 41 \n",
"173 Perempuan 21 1.540000 47 \n",
"510 Perempuan 25 1.643548 62 \n",
"548 Perempuan 21 1.641347 66 \n",
"389 Laki-laki 39 1.720000 86 \n",
"394 Perempuan 37 1.560000 77 \n",
"206 Perempuan 18 1.640000 59 \n",
"295 Perempuan 19 1.680000 49 \n",
"480 Perempuan 21 1.694749 49 \n",
"124 Perempuan 20 1.630000 64 \n",
"\n",
" histori_keluarga_kelebihan_BB konsumsi_tinggi_kalori konsumsi_sayuran \\\n",
"606 Ya Ya Kadang-kadang \n",
"71 Ya Ya Selalu \n",
"609 Tidak Ya Selalu \n",
"678 Ya Ya Kadang-kadang \n",
"644 Ya Ya Kadang-kadang \n",
"275 Tidak Ya Selalu \n",
"173 Ya Tidak Selalu \n",
"510 Tidak Tidak Kadang-kadang \n",
"548 Ya Ya Selalu \n",
"389 Ya Ya Selalu \n",
"394 Ya Ya Kadang-kadang \n",
"206 Ya Ya Kadang-kadang \n",
"295 Tidak Tidak Selalu \n",
"480 Ya Ya Selalu \n",
"124 Ya Ya Tidak pernah \n",
"\n",
" makan_berat ngemil merokok konsumsi_air_liter pemantauan_kalori \\\n",
"606 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"71 3x Sering Ya Lebih 2 liter Ya \n",
"609 1-2x Kadang-kadang Tidak Lebih 2 liter Tidak \n",
"678 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"644 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"275 1-2x Sering Tidak 1-2 liter Tidak \n",
"173 3x Selalu Tidak 1-2 liter Tidak \n",
"510 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"548 1-2x Kadang-kadang Tidak 1-2 liter Tidak \n",
"389 1-2x Kadang-kadang Tidak 1-2 liter Tidak \n",
"394 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"206 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"295 3x Kadang-kadang Tidak 1-2 liter Tidak \n",
"480 3x Sering Tidak 1-2 liter Tidak \n",
"124 3x Selalu Tidak 1-2 liter Tidak \n",
"\n",
" aktifitas_fisik penggunaan_perangkat_teknologi konsumsi_alkohol \\\n",
"606 Tidak pernah 0-2 jam Kadang-kadang \n",
"71 1-2 hari 3-5 jam Sering \n",
"609 Tidak pernah 0-2 jam Tidak pernah \n",
"678 Tidak pernah 0-2 jam Kadang-kadang \n",
"644 Tidak pernah 0-2 jam Kadang-kadang \n",
"275 Tidak pernah 0-2 jam Kadang-kadang \n",
"173 2-4 hari 0-2 jam Tidak pernah \n",
"510 1-2 hari 0-2 jam Tidak pernah \n",
"548 Tidak pernah 0-2 jam Tidak pernah \n",
"389 Tidak pernah 0-2 jam Tidak pernah \n",
"394 Tidak pernah 0-2 jam Kadang-kadang \n",
"206 1-2 hari 0-2 jam Kadang-kadang \n",
"295 1-2 hari 0-2 jam Kadang-kadang \n",
"480 Tidak pernah 0-2 jam Tidak pernah \n",
"124 Tidak pernah 3-5 jam Tidak pernah \n",
"\n",
" transporasi_biasa_digunakan kelas_obesitas \\\n",
"606 Jalan kaki obesitas_I \n",
"71 Sepeda motor normal \n",
"609 Jalan kaki obesitas_I \n",
"678 Jalan kaki obesitas_II \n",
"644 Jalan kaki obesitas_II \n",
"275 Sepeda motor berat_badan_kurang \n",
"173 Sepeda motor normal \n",
"510 Mobil kelebihan_berat_badan \n",
"548 Sepeda motor kelebihan_berat_badan \n",
"389 Jalan kaki obesitas_I \n",
"394 Jalan kaki obesitas_II \n",
"206 Sepeda motor normal \n",
"295 Sepeda motor berat_badan_kurang \n",
"480 Sepeda motor berat_badan_kurang \n",
"124 Jalan kaki kelebihan_berat_badan \n",
"\n",
" klasifikasi_naive_bayes klasifikasi_k_nearest_neighbor \n",
"606 obesitas_II obesitas_I \n",
"71 normal normal \n",
"609 obesitas_I obesitas_I \n",
"678 obesitas_II obesitas_II \n",
"644 obesitas_II obesitas_II \n",
"275 berat_badan_kurang berat_badan_kurang \n",
"173 berat_badan_kurang normal \n",
"510 kelebihan_berat_badan kelebihan_berat_badan \n",
"548 obesitas_II kelebihan_berat_badan \n",
"389 obesitas_II obesitas_I \n",
"394 obesitas_II obesitas_II \n",
"206 kelebihan_berat_badan normal \n",
"295 berat_badan_kurang berat_badan_kurang \n",
"480 berat_badan_kurang berat_badan_kurang \n",
"124 normal kelebihan_berat_badan "
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_NV_KNN['klasifikasi_naive_bayes'] = Y_predictNV\n",
"data_NV_KNN['klasifikasi_k_nearest_neighbor'] = Y_predictKNN\n",
"data_NV_KNN"
]
},
{
"cell_type": "markdown",
"id": "6eb6c4ab",
"metadata": {},
"source": [
"### download data hasil klasifikasi"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "caafc24e",
"metadata": {},
"outputs": [],
"source": [
"# excel_file = pd.ExcelWriter(\"smote_data_hasil_klasifikasi.xlsx\")\n",
"# data_NV_KNN.to_excel(excel_file)\n",
"# excel_file.save()"
]
},
{
"cell_type": "markdown",
"id": "ddd2decc",
"metadata": {},
"source": [
"## Visualisasi data hasil klasifikasi"
]
},
{
"cell_type": "code",
"execution_count": 52,
"id": "01a3ab8e",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>kelas_obesitas</th>\n",
" <th>keterangan</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>obesitas_I</td>\n",
" <td>kelas_sebenarnya</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>normal</td>\n",
" <td>kelas_sebenarnya</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>obesitas_I</td>\n",
" <td>kelas_sebenarnya</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>obesitas_II</td>\n",
" <td>kelas_sebenarnya</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>obesitas_II</td>\n",
" <td>kelas_sebenarnya</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>berat_badan_kurang</td>\n",
" <td>kelas_sebenarnya</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>normal</td>\n",
" <td>kelas_sebenarnya</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>kelas_sebenarnya</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>kelas_sebenarnya</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>obesitas_I</td>\n",
" <td>kelas_sebenarnya</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>obesitas_II</td>\n",
" <td>kelas_sebenarnya</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>normal</td>\n",
" <td>kelas_sebenarnya</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>berat_badan_kurang</td>\n",
" <td>kelas_sebenarnya</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>berat_badan_kurang</td>\n",
" <td>kelas_sebenarnya</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>kelas_sebenarnya</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>obesitas_II</td>\n",
" <td>klasifikasi_naive_bayes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>normal</td>\n",
" <td>klasifikasi_naive_bayes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>obesitas_I</td>\n",
" <td>klasifikasi_naive_bayes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>obesitas_II</td>\n",
" <td>klasifikasi_naive_bayes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>obesitas_II</td>\n",
" <td>klasifikasi_naive_bayes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>berat_badan_kurang</td>\n",
" <td>klasifikasi_naive_bayes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>berat_badan_kurang</td>\n",
" <td>klasifikasi_naive_bayes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>klasifikasi_naive_bayes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>obesitas_II</td>\n",
" <td>klasifikasi_naive_bayes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>obesitas_II</td>\n",
" <td>klasifikasi_naive_bayes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>obesitas_II</td>\n",
" <td>klasifikasi_naive_bayes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>klasifikasi_naive_bayes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>berat_badan_kurang</td>\n",
" <td>klasifikasi_naive_bayes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>berat_badan_kurang</td>\n",
" <td>klasifikasi_naive_bayes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>normal</td>\n",
" <td>klasifikasi_naive_bayes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>obesitas_I</td>\n",
" <td>klasifikasi_k_nearest_neighbor</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>normal</td>\n",
" <td>klasifikasi_k_nearest_neighbor</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>obesitas_I</td>\n",
" <td>klasifikasi_k_nearest_neighbor</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>obesitas_II</td>\n",
" <td>klasifikasi_k_nearest_neighbor</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>obesitas_II</td>\n",
" <td>klasifikasi_k_nearest_neighbor</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>berat_badan_kurang</td>\n",
" <td>klasifikasi_k_nearest_neighbor</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>normal</td>\n",
" <td>klasifikasi_k_nearest_neighbor</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>klasifikasi_k_nearest_neighbor</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>klasifikasi_k_nearest_neighbor</td>\n",
" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td>obesitas_I</td>\n",
" <td>klasifikasi_k_nearest_neighbor</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>obesitas_II</td>\n",
" <td>klasifikasi_k_nearest_neighbor</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41</th>\n",
" <td>normal</td>\n",
" <td>klasifikasi_k_nearest_neighbor</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td>berat_badan_kurang</td>\n",
" <td>klasifikasi_k_nearest_neighbor</td>\n",
" </tr>\n",
" <tr>\n",
" <th>43</th>\n",
" <td>berat_badan_kurang</td>\n",
" <td>klasifikasi_k_nearest_neighbor</td>\n",
" </tr>\n",
" <tr>\n",
" <th>44</th>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>klasifikasi_k_nearest_neighbor</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" kelas_obesitas keterangan\n",
"0 obesitas_I kelas_sebenarnya\n",
"1 normal kelas_sebenarnya\n",
"2 obesitas_I kelas_sebenarnya\n",
"3 obesitas_II kelas_sebenarnya\n",
"4 obesitas_II kelas_sebenarnya\n",
"5 berat_badan_kurang kelas_sebenarnya\n",
"6 normal kelas_sebenarnya\n",
"7 kelebihan_berat_badan kelas_sebenarnya\n",
"8 kelebihan_berat_badan kelas_sebenarnya\n",
"9 obesitas_I kelas_sebenarnya\n",
"10 obesitas_II kelas_sebenarnya\n",
"11 normal kelas_sebenarnya\n",
"12 berat_badan_kurang kelas_sebenarnya\n",
"13 berat_badan_kurang kelas_sebenarnya\n",
"14 kelebihan_berat_badan kelas_sebenarnya\n",
"15 obesitas_II klasifikasi_naive_bayes\n",
"16 normal klasifikasi_naive_bayes\n",
"17 obesitas_I klasifikasi_naive_bayes\n",
"18 obesitas_II klasifikasi_naive_bayes\n",
"19 obesitas_II klasifikasi_naive_bayes\n",
"20 berat_badan_kurang klasifikasi_naive_bayes\n",
"21 berat_badan_kurang klasifikasi_naive_bayes\n",
"22 kelebihan_berat_badan klasifikasi_naive_bayes\n",
"23 obesitas_II klasifikasi_naive_bayes\n",
"24 obesitas_II klasifikasi_naive_bayes\n",
"25 obesitas_II klasifikasi_naive_bayes\n",
"26 kelebihan_berat_badan klasifikasi_naive_bayes\n",
"27 berat_badan_kurang klasifikasi_naive_bayes\n",
"28 berat_badan_kurang klasifikasi_naive_bayes\n",
"29 normal klasifikasi_naive_bayes\n",
"30 obesitas_I klasifikasi_k_nearest_neighbor\n",
"31 normal klasifikasi_k_nearest_neighbor\n",
"32 obesitas_I klasifikasi_k_nearest_neighbor\n",
"33 obesitas_II klasifikasi_k_nearest_neighbor\n",
"34 obesitas_II klasifikasi_k_nearest_neighbor\n",
"35 berat_badan_kurang klasifikasi_k_nearest_neighbor\n",
"36 normal klasifikasi_k_nearest_neighbor\n",
"37 kelebihan_berat_badan klasifikasi_k_nearest_neighbor\n",
"38 kelebihan_berat_badan klasifikasi_k_nearest_neighbor\n",
"39 obesitas_I klasifikasi_k_nearest_neighbor\n",
"40 obesitas_II klasifikasi_k_nearest_neighbor\n",
"41 normal klasifikasi_k_nearest_neighbor\n",
"42 berat_badan_kurang klasifikasi_k_nearest_neighbor\n",
"43 berat_badan_kurang klasifikasi_k_nearest_neighbor\n",
"44 kelebihan_berat_badan klasifikasi_k_nearest_neighbor"
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_ringkasan = pd.DataFrame(columns=['kelas_obesitas', 'keterangan'])\n",
"\n",
"# Menggabungkan nilai dari kolom obesity_class\n",
"data_ringkasan = pd.concat([data_ringkasan, pd.DataFrame({'kelas_obesitas': data_NV_KNN['kelas_obesitas'], 'keterangan': 'kelas_sebenarnya'})], ignore_index=True)\n",
"\n",
"# Menggabungkan nilai dari kolom klasifikasi_naive_bayes\n",
"data_ringkasan = pd.concat([data_ringkasan, pd.DataFrame({'kelas_obesitas': data_NV_KNN['klasifikasi_naive_bayes'], 'keterangan': 'klasifikasi_naive_bayes'})], ignore_index=True)\n",
"\n",
"# Menggabungkan nilai dari kolom klasifikasi_k_nearest_neighbor\n",
"data_ringkasan = pd.concat([data_ringkasan, pd.DataFrame({'kelas_obesitas': data_NV_KNN['klasifikasi_k_nearest_neighbor'], 'keterangan': 'klasifikasi_k_nearest_neighbor'})], ignore_index=True)\n",
"\n",
"data_ringkasan"
]
},
{
"cell_type": "code",
"execution_count": 53,
"id": "7383d81d",
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 900x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(9,6))\n",
"sns.countplot(x='kelas_obesitas', hue='keterangan', data=data_ringkasan, order=urutan_obesitas, palette='rocket_r')\n",
"# plt.xticks(rotation=20, ha='right')\n",
"# plt.tight_layout()\n",
"plt.xlabel('kelas_obesitas', labelpad=6) # Add padding to the x-axis label\n",
"plt.ylabel('jumlah', labelpad=5) # Add padding to the x-axis label\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "9a25d803",
"metadata": {},
"source": [
"### Pembuktian visualisasi data hasil klasifikasi"
]
},
{
"cell_type": "code",
"execution_count": 54,
"id": "e1ab2eb5",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>kelas_obesitas</th>\n",
" <th>jumlah</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>berat_badan_kurang</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>normal</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>obesitas_I</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>obesitas_II</td>\n",
" <td>3</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" kelas_obesitas jumlah\n",
"3 berat_badan_kurang 3\n",
"1 normal 3\n",
"4 kelebihan_berat_badan 3\n",
"0 obesitas_I 3\n",
"2 obesitas_II 3"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"kelas_obesitashasil = data_NV_KNN['kelas_obesitas'].value_counts().rename_axis('kelas_obesitas').reset_index(name='jumlah')\n",
"kelas_obesitashasil['kelas_obesitas'] = pd.Categorical(kelas_obesitashasil['kelas_obesitas'], categories=urutan_obesitas, ordered=True)\n",
"kelas_obesitashasil = kelas_obesitashasil.sort_values(by='kelas_obesitas')\n",
"kelas_obesitashasil"
]
},
{
"cell_type": "code",
"execution_count": 55,
"id": "8bb32b20",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>klasifikasi_naive_bayes</th>\n",
" <th>jumlah</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>berat_badan_kurang</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>normal</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>obesitas_I</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>obesitas_II</td>\n",
" <td>6</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" klasifikasi_naive_bayes jumlah\n",
"1 berat_badan_kurang 4\n",
"2 normal 2\n",
"3 kelebihan_berat_badan 2\n",
"4 obesitas_I 1\n",
"0 obesitas_II 6"
]
},
"execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"kelas_obesitashasilNV = data_NV_KNN['klasifikasi_naive_bayes'].value_counts().rename_axis('klasifikasi_naive_bayes').reset_index(name='jumlah')\n",
"kelas_obesitashasilNV['klasifikasi_naive_bayes'] = pd.Categorical(kelas_obesitashasilNV['klasifikasi_naive_bayes'], categories=urutan_obesitas, ordered=True)\n",
"kelas_obesitashasilNV = kelas_obesitashasilNV.sort_values(by='klasifikasi_naive_bayes')\n",
"kelas_obesitashasilNV"
]
},
{
"cell_type": "code",
"execution_count": 56,
"id": "4e14fdd9",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>klasifikasi_k_nearest_neighbor</th>\n",
" <th>jumlah</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>berat_badan_kurang</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>normal</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>kelebihan_berat_badan</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>obesitas_I</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>obesitas_II</td>\n",
" <td>3</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" klasifikasi_k_nearest_neighbor jumlah\n",
"3 berat_badan_kurang 3\n",
"1 normal 3\n",
"4 kelebihan_berat_badan 3\n",
"0 obesitas_I 3\n",
"2 obesitas_II 3"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"kelas_obesitashasilKNN = data_NV_KNN['klasifikasi_k_nearest_neighbor'].value_counts().rename_axis('klasifikasi_k_nearest_neighbor').reset_index(name='jumlah')\n",
"kelas_obesitashasilKNN['klasifikasi_k_nearest_neighbor'] = pd.Categorical(kelas_obesitashasilKNN['klasifikasi_k_nearest_neighbor'], categories=urutan_obesitas, ordered=True)\n",
"kelas_obesitashasilKNN = kelas_obesitashasilKNN.sort_values(by='klasifikasi_k_nearest_neighbor')\n",
"kelas_obesitashasilKNN"
]
},
{
"cell_type": "markdown",
"id": "9e12d052",
"metadata": {},
"source": [
"# Analisis perbandingan hasil"
]
},
{
"cell_type": "code",
"execution_count": 57,
"id": "c50b3c45",
"metadata": {},
"outputs": [
{
"data": {
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"<table border=\"1\" class=\"dataframe\">\n",
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>testing</th>\n",
" <th>data_latih</th>\n",
" <th>data_uji</th>\n",
" <th>latih_uji</th>\n",
" <th>model</th>\n",
" <th>akurasi</th>\n",
" <th>presisi</th>\n",
" <th>recal</th>\n",
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" <th>w_latih</th>\n",
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" <th>roc_auc</th>\n",
" <th>Unnamed: 13</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0.90</td>\n",
" <td>70.0</td>\n",
" <td>635.0</td>\n",
" <td>70:635</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.47</td>\n",
" <td>0.44</td>\n",
" <td>0.47</td>\n",
" <td>0.41</td>\n",
" <td>0.004090</td>\n",
" <td>0.002630</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <th>1</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>70:635</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.62</td>\n",
" <td>0.60</td>\n",
" <td>0.62</td>\n",
" <td>0.60</td>\n",
" <td>0.001189</td>\n",
" <td>0.105440</td>\n",
" <td>4.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.80</td>\n",
" <td>141.0</td>\n",
" <td>564.0</td>\n",
" <td>141:594</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.51</td>\n",
" <td>0.51</td>\n",
" <td>0.51</td>\n",
" <td>0.45</td>\n",
" <td>0.008121</td>\n",
" <td>0.002256</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>141:594</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.63</td>\n",
" <td>0.63</td>\n",
" <td>0.63</td>\n",
" <td>0.63</td>\n",
" <td>0.001047</td>\n",
" <td>0.093908</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.70</td>\n",
" <td>211.0</td>\n",
" <td>494.0</td>\n",
" <td>211:494</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.55</td>\n",
" <td>0.51</td>\n",
" <td>0.55</td>\n",
" <td>0.48</td>\n",
" <td>0.008355</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>211:494</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.66</td>\n",
" <td>0.66</td>\n",
" <td>0.66</td>\n",
" <td>0.66</td>\n",
" <td>0.001281</td>\n",
" <td>0.070467</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>0.60</td>\n",
" <td>282.0</td>\n",
" <td>432.0</td>\n",
" <td>282:432</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.51</td>\n",
" <td>0.53</td>\n",
" <td>0.51</td>\n",
" <td>0.46</td>\n",
" <td>0.008337</td>\n",
" <td>0.001994</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>282:432</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.70</td>\n",
" <td>0.71</td>\n",
" <td>0.70</td>\n",
" <td>0.69</td>\n",
" <td>0.001401</td>\n",
" <td>0.072488</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.50</td>\n",
" <td>352.0</td>\n",
" <td>353.0</td>\n",
" <td>352:353</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.54</td>\n",
" <td>0.54</td>\n",
" <td>0.54</td>\n",
" <td>0.54</td>\n",
" <td>0.008823</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>352:353</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.71</td>\n",
" <td>0.72</td>\n",
" <td>0.71</td>\n",
" <td>0.70</td>\n",
" <td>0.001383</td>\n",
" <td>0.070567</td>\n",
" <td>4.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.40</td>\n",
" <td>423.0</td>\n",
" <td>282.0</td>\n",
" <td>423:282</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.51</td>\n",
" <td>0.50</td>\n",
" <td>0.51</td>\n",
" <td>0.45</td>\n",
" <td>0.008008</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>423:282</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.75</td>\n",
" <td>0.75</td>\n",
" <td>0.75</td>\n",
" <td>0.73</td>\n",
" <td>0.000000</td>\n",
" <td>0.069703</td>\n",
" <td>4.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>0.30</td>\n",
" <td>493.0</td>\n",
" <td>212.0</td>\n",
" <td>493:212</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.65</td>\n",
" <td>0.65</td>\n",
" <td>0.65</td>\n",
" <td>0.62</td>\n",
" <td>0.009819</td>\n",
" <td>0.001983</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>493:212</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.77</td>\n",
" <td>0.77</td>\n",
" <td>0.77</td>\n",
" <td>0.77</td>\n",
" <td>0.001301</td>\n",
" <td>0.064058</td>\n",
" <td>4.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>0.20</td>\n",
" <td>564.0</td>\n",
" <td>141.0</td>\n",
" <td>564:141</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.65</td>\n",
" <td>0.70</td>\n",
" <td>0.65</td>\n",
" <td>0.62</td>\n",
" <td>0.009426</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NV</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>564:141</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.79</td>\n",
" <td>0.79</td>\n",
" <td>0.79</td>\n",
" <td>0.78</td>\n",
" <td>0.000000</td>\n",
" <td>0.055702</td>\n",
" <td>4.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0.10</td>\n",
" <td>634.0</td>\n",
" <td>71.0</td>\n",
" <td>634:71</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.63</td>\n",
" <td>0.63</td>\n",
" <td>0.63</td>\n",
" <td>0.59</td>\n",
" <td>0.009813</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>634:71</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.83</td>\n",
" <td>0.83</td>\n",
" <td>0.83</td>\n",
" <td>0.82</td>\n",
" <td>0.001507</td>\n",
" <td>0.044852</td>\n",
" <td>4.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>0.09</td>\n",
" <td>641.0</td>\n",
" <td>64.0</td>\n",
" <td>641:64</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.62</td>\n",
" <td>0.71</td>\n",
" <td>0.62</td>\n",
" <td>0.59</td>\n",
" <td>0.009722</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>641:64</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.80</td>\n",
" <td>0.79</td>\n",
" <td>0.79</td>\n",
" <td>0.79</td>\n",
" <td>0.002041</td>\n",
" <td>0.046776</td>\n",
" <td>6.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>0.08</td>\n",
" <td>648.0</td>\n",
" <td>57.0</td>\n",
" <td>648:57</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.63</td>\n",
" <td>0.71</td>\n",
" <td>0.63</td>\n",
" <td>0.60</td>\n",
" <td>0.013452</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>648:57</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.81</td>\n",
" <td>0.80</td>\n",
" <td>0.80</td>\n",
" <td>0.80</td>\n",
" <td>0.002641</td>\n",
" <td>0.037296</td>\n",
" <td>6.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>0.07</td>\n",
" <td>655.0</td>\n",
" <td>50.0</td>\n",
" <td>655:50</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.60</td>\n",
" <td>0.69</td>\n",
" <td>0.60</td>\n",
" <td>0.55</td>\n",
" <td>0.012512</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>655:50</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.84</td>\n",
" <td>0.84</td>\n",
" <td>0.84</td>\n",
" <td>0.84</td>\n",
" <td>0.002730</td>\n",
" <td>0.029474</td>\n",
" <td>6.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>0.06</td>\n",
" <td>662.0</td>\n",
" <td>43.0</td>\n",
" <td>662:43</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.60</td>\n",
" <td>0.70</td>\n",
" <td>0.61</td>\n",
" <td>0.56</td>\n",
" <td>0.014257</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>662:43</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.84</td>\n",
" <td>0.84</td>\n",
" <td>0.83</td>\n",
" <td>0.83</td>\n",
" <td>0.002500</td>\n",
" <td>0.028498</td>\n",
" <td>6.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>0.05</td>\n",
" <td>669.0</td>\n",
" <td>36.0</td>\n",
" <td>669:36</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.61</td>\n",
" <td>0.69</td>\n",
" <td>0.60</td>\n",
" <td>0.57</td>\n",
" <td>0.015503</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>669:36</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.81</td>\n",
" <td>0.81</td>\n",
" <td>0.80</td>\n",
" <td>0.80</td>\n",
" <td>0.002558</td>\n",
" <td>0.025552</td>\n",
" <td>6.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>0.04</td>\n",
" <td>676.0</td>\n",
" <td>29.0</td>\n",
" <td>676:29</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.55</td>\n",
" <td>0.62</td>\n",
" <td>0.55</td>\n",
" <td>0.51</td>\n",
" <td>0.016332</td>\n",
" <td>0.000171</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>676:29</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.76</td>\n",
" <td>0.75</td>\n",
" <td>0.75</td>\n",
" <td>0.75</td>\n",
" <td>0.002468</td>\n",
" <td>0.025420</td>\n",
" <td>6.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>0.03</td>\n",
" <td>683.0</td>\n",
" <td>22.0</td>\n",
" <td>683:22</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.50</td>\n",
" <td>0.54</td>\n",
" <td>0.49</td>\n",
" <td>0.45</td>\n",
" <td>0.017306</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>683:22</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>0.77</td>\n",
" <td>0.81</td>\n",
" <td>0.76</td>\n",
" <td>0.76</td>\n",
" <td>0.002051</td>\n",
" <td>0.025016</td>\n",
" <td>7.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>0.02</td>\n",
" <td>690.0</td>\n",
" <td>15.0</td>\n",
" <td>690:15</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.60</td>\n",
" <td>0.65</td>\n",
" <td>0.60</td>\n",
" <td>0.56</td>\n",
" <td>0.018635</td>\n",
" <td>0.000251</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>KNN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>690:15</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>1.00</td>\n",
" <td>1.00</td>\n",
" <td>1.00</td>\n",
" <td>1.00</td>\n",
" <td>0.002551</td>\n",
" <td>0.024966</td>\n",
" <td>7.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>0.01</td>\n",
" <td>697.0</td>\n",
" <td>8.0</td>\n",
" <td>697:8</td>\n",
" <td>naive_bayes</td>\n",
" <td>0.62</td>\n",
" <td>0.63</td>\n",
" <td>0.60</td>\n",
" <td>0.56</td>\n",
" <td>0.019062</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>697:8</td>\n",
" <td>k_nearest_neighbor</td>\n",
" <td>1.00</td>\n",
" <td>1.00</td>\n",
" <td>1.00</td>\n",
" <td>1.00</td>\n",
" <td>0.003400</td>\n",
" <td>0.018389</td>\n",
" <td>7.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" testing data_latih data_uji latih_uji model akurasi \\\n",
"0 0.90 70.0 635.0 70:635 naive_bayes 0.47 \n",
"1 NaN NaN NaN 70:635 k_nearest_neighbor 0.62 \n",
"2 0.80 141.0 564.0 141:594 naive_bayes 0.51 \n",
"3 NaN NaN NaN 141:594 k_nearest_neighbor 0.63 \n",
"4 0.70 211.0 494.0 211:494 naive_bayes 0.55 \n",
"5 NaN NaN NaN 211:494 k_nearest_neighbor 0.66 \n",
"6 0.60 282.0 432.0 282:432 naive_bayes 0.51 \n",
"7 NaN NaN NaN 282:432 k_nearest_neighbor 0.70 \n",
"8 0.50 352.0 353.0 352:353 naive_bayes 0.54 \n",
"9 NaN NaN NaN 352:353 k_nearest_neighbor 0.71 \n",
"10 0.40 423.0 282.0 423:282 naive_bayes 0.51 \n",
"11 NaN NaN NaN 423:282 k_nearest_neighbor 0.75 \n",
"12 0.30 493.0 212.0 493:212 naive_bayes 0.65 \n",
"13 NaN NaN NaN 493:212 k_nearest_neighbor 0.77 \n",
"14 0.20 564.0 141.0 564:141 naive_bayes 0.65 \n",
"15 NaN NaN NaN 564:141 k_nearest_neighbor 0.79 \n",
"16 0.10 634.0 71.0 634:71 naive_bayes 0.63 \n",
"17 NaN NaN NaN 634:71 k_nearest_neighbor 0.83 \n",
"18 0.09 641.0 64.0 641:64 naive_bayes 0.62 \n",
"19 NaN NaN NaN 641:64 k_nearest_neighbor 0.80 \n",
"20 0.08 648.0 57.0 648:57 naive_bayes 0.63 \n",
"21 NaN NaN NaN 648:57 k_nearest_neighbor 0.81 \n",
"22 0.07 655.0 50.0 655:50 naive_bayes 0.60 \n",
"23 NaN NaN NaN 655:50 k_nearest_neighbor 0.84 \n",
"24 0.06 662.0 43.0 662:43 naive_bayes 0.60 \n",
"25 NaN NaN NaN 662:43 k_nearest_neighbor 0.84 \n",
"26 0.05 669.0 36.0 669:36 naive_bayes 0.61 \n",
"27 NaN NaN NaN 669:36 k_nearest_neighbor 0.81 \n",
"28 0.04 676.0 29.0 676:29 naive_bayes 0.55 \n",
"29 NaN NaN NaN 676:29 k_nearest_neighbor 0.76 \n",
"30 0.03 683.0 22.0 683:22 naive_bayes 0.50 \n",
"31 NaN NaN NaN 683:22 k_nearest_neighbor 0.77 \n",
"32 0.02 690.0 15.0 690:15 naive_bayes 0.60 \n",
"33 NaN NaN NaN 690:15 k_nearest_neighbor 1.00 \n",
"34 0.01 697.0 8.0 697:8 naive_bayes 0.62 \n",
"35 NaN NaN NaN 697:8 k_nearest_neighbor 1.00 \n",
"\n",
" presisi recal F1 w_latih w_uji k_knn roc_auc Unnamed: 13 \n",
"0 0.44 0.47 0.41 0.004090 0.002630 NaN NaN NaN \n",
"1 0.60 0.62 0.60 0.001189 0.105440 4.0 NaN NaN \n",
"2 0.51 0.51 0.45 0.008121 0.002256 NaN NaN NaN \n",
"3 0.63 0.63 0.63 0.001047 0.093908 3.0 NaN NaN \n",
"4 0.51 0.55 0.48 0.008355 0.000000 NaN NaN NaN \n",
"5 0.66 0.66 0.66 0.001281 0.070467 3.0 NaN NaN \n",
"6 0.53 0.51 0.46 0.008337 0.001994 NaN NaN NaN \n",
"7 0.71 0.70 0.69 0.001401 0.072488 3.0 NaN NaN \n",
"8 0.54 0.54 0.54 0.008823 0.000000 NaN NaN NaN \n",
"9 0.72 0.71 0.70 0.001383 0.070567 4.0 NaN NaN \n",
"10 0.50 0.51 0.45 0.008008 0.000000 NaN NaN NaN \n",
"11 0.75 0.75 0.73 0.000000 0.069703 4.0 NaN NaN \n",
"12 0.65 0.65 0.62 0.009819 0.001983 NaN NaN NaN \n",
"13 0.77 0.77 0.77 0.001301 0.064058 4.0 NaN NaN \n",
"14 0.70 0.65 0.62 0.009426 0.000000 NaN NaN NV \n",
"15 0.79 0.79 0.78 0.000000 0.055702 4.0 NaN NaN \n",
"16 0.63 0.63 0.59 0.009813 0.000000 NaN NaN NaN \n",
"17 0.83 0.83 0.82 0.001507 0.044852 4.0 NaN NaN \n",
"18 0.71 0.62 0.59 0.009722 0.000000 NaN NaN NaN \n",
"19 0.79 0.79 0.79 0.002041 0.046776 6.0 NaN NaN \n",
"20 0.71 0.63 0.60 0.013452 0.000000 NaN NaN NaN \n",
"21 0.80 0.80 0.80 0.002641 0.037296 6.0 NaN NaN \n",
"22 0.69 0.60 0.55 0.012512 0.000000 NaN NaN NaN \n",
"23 0.84 0.84 0.84 0.002730 0.029474 6.0 NaN NaN \n",
"24 0.70 0.61 0.56 0.014257 0.000000 NaN NaN NaN \n",
"25 0.84 0.83 0.83 0.002500 0.028498 6.0 NaN NaN \n",
"26 0.69 0.60 0.57 0.015503 0.000000 NaN NaN NaN \n",
"27 0.81 0.80 0.80 0.002558 0.025552 6.0 NaN NaN \n",
"28 0.62 0.55 0.51 0.016332 0.000171 NaN NaN NaN \n",
"29 0.75 0.75 0.75 0.002468 0.025420 6.0 NaN NaN \n",
"30 0.54 0.49 0.45 0.017306 0.000000 NaN NaN NaN \n",
"31 0.81 0.76 0.76 0.002051 0.025016 7.0 NaN NaN \n",
"32 0.65 0.60 0.56 0.018635 0.000251 NaN NaN KNN \n",
"33 1.00 1.00 1.00 0.002551 0.024966 7.0 NaN NaN \n",
"34 0.63 0.60 0.56 0.019062 0.000000 NaN NaN NaN \n",
"35 1.00 1.00 1.00 0.003400 0.018389 7.0 NaN NaN "
]
},
"execution_count": 57,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataperbandingan = pd.read_excel('dataset/smote_perbandingan.xlsx')\n",
"dataperbandingan"
]
},
{
"cell_type": "code",
"execution_count": 58,
"id": "53e49972",
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 1200x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set_style(\"whitegrid\")\n",
"plt.figure(figsize=(12, 5))\n",
"\n",
"colors = {'naive_bayes': '#FF9800', 'k_nearest_neighbor': '#F7C566'}\n",
"sns.lineplot(x='latih_uji', y='akurasi', hue='model', data=dataperbandingan, markers=True, palette=colors)\n",
"sns.scatterplot(x='latih_uji', y='akurasi', hue='model', data=dataperbandingan, marker='o', s=40, legend=False, palette=colors)\n",
"\n",
"plt.grid(alpha=0.4)\n",
"plt.title('Akurasi Berdasarkan Rasio Data Latih dan Data Uji Setiap Model Klasifikasi')\n",
"plt.xlabel('Perbandingan Data Latih dan Data Uji')\n",
"plt.xticks(rotation=30, ha='right')\n",
"plt.ylabel('Akurasi')\n",
"plt.legend(title='Model')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 59,
"id": "35ea8c4b",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1200x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set_style(\"whitegrid\")\n",
"plt.figure(figsize=(12, 5))\n",
"\n",
"colors = {'naive_bayes': '#FF9800', 'k_nearest_neighbor': '#F7C566'}\n",
"sns.lineplot(x='latih_uji', y='presisi', hue='model', data=dataperbandingan, markers=True, palette=colors)\n",
"sns.scatterplot(x='latih_uji', y='presisi', hue='model', data=dataperbandingan, marker='o', s=40, legend=False, palette=colors)\n",
"\n",
"plt.grid(alpha=0.4)\n",
"plt.title('Presisi Berdasarkan Rasio Data Latih dan Data Uji Setiap Model Klasifikasi')\n",
"plt.xlabel('Perbandingan Data Latih dan Data Uji')\n",
"plt.xticks(rotation=30, ha='right')\n",
"plt.ylabel('Presisi')\n",
"plt.legend(title='Model')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 60,
"id": "d95a268b",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1200x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set_style(\"whitegrid\")\n",
"plt.figure(figsize=(12, 5))\n",
"\n",
"colors = {'naive_bayes': '#FF9800', 'k_nearest_neighbor': '#F7C566'}\n",
"sns.lineplot(x='latih_uji', y='recal', hue='model', data=dataperbandingan, markers=True, palette=colors)\n",
"sns.scatterplot(x='latih_uji', y='recal', hue='model', data=dataperbandingan, marker='o', s=40, legend=False, palette=colors)\n",
"\n",
"plt.grid(alpha=0.4)\n",
"plt.title('Recal Berdasarkan Rasio Data Latih dan Data Uji Setiap Model Klasifikasi')\n",
"plt.xlabel('Perbandingan Data Latih dan Data Uji')\n",
"plt.xticks(rotation=30, ha='right')\n",
"plt.ylabel('Recal')\n",
"plt.legend(title='Model')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 61,
"id": "da7fd90e",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1200x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set_style(\"whitegrid\")\n",
"plt.figure(figsize=(12, 5))\n",
"\n",
"colors = {'naive_bayes': '#FF9800', 'k_nearest_neighbor': '#F7C566'}\n",
"sns.lineplot(x='latih_uji', y='F1', hue='model', data=dataperbandingan, markers=True, palette=colors)\n",
"sns.scatterplot(x='latih_uji', y='F1', hue='model', data=dataperbandingan, marker='o', s=40, legend=False, palette=colors)\n",
"\n",
"plt.grid(alpha=0.4)\n",
"plt.title('Skor F1 Berdasarkan Rasio Data Latih dan Data Uji Setiap Model Klasifikasi')\n",
"plt.xlabel('Perbandingan Data Latih dan Data Uji')\n",
"plt.xticks(rotation=30, ha='right')\n",
"plt.ylabel('Skor F1')\n",
"plt.legend(title='Model')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 62,
"id": "0de27e9b",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1200x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set_style(\"whitegrid\")\n",
"plt.figure(figsize=(12, 5))\n",
"\n",
"colors = {'naive_bayes': '#FF9800', 'k_nearest_neighbor': '#F7C566'}\n",
"sns.lineplot(x='latih_uji', y='w_latih', hue='model', data=dataperbandingan, markers=True, palette=colors)\n",
"sns.scatterplot(x='latih_uji', y='w_latih', hue='model', data=dataperbandingan, marker='o', s=40, legend=False, palette=colors)\n",
"\n",
"plt.grid(alpha=0.4)\n",
"plt.title('Waktu Pelatihan Berdasarkan Rasio Data Latih dan Data Uji Setiap Model Klasifikasi')\n",
"plt.xlabel('Perbandingan Data Latih dan Data Uji')\n",
"plt.xticks(rotation=30, ha='right')\n",
"plt.ylabel('Waktu Pelatihan')\n",
"plt.legend(title='Model')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 63,
"id": "2472d6ad",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1200x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set_style(\"whitegrid\")\n",
"plt.figure(figsize=(12, 5))\n",
"\n",
"colors = {'naive_bayes': '#FF9800', 'k_nearest_neighbor': '#F7C566'}\n",
"sns.lineplot(x='latih_uji', y='w_uji', hue='model', data=dataperbandingan, markers=True, palette=colors)\n",
"sns.scatterplot(x='latih_uji', y='w_uji', hue='model', data=dataperbandingan, marker='o', s=40, legend=False, palette=colors)\n",
"\n",
"plt.grid(alpha=0.4)\n",
"plt.title('Waktu Pengujian Berdasarkan Rasio Data Latih dan Data Uji Setiap Model Klasifikasi')\n",
"plt.xlabel('Perbandingan Data Latih dan Data Uji')\n",
"plt.xticks(rotation=30, ha='right')\n",
"plt.ylabel('Waktu Pengujian')\n",
"plt.legend(title='Model')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "4e1136a4",
"metadata": {},
"source": [
"## Analisis perbandingan hasil setiap algoritma"
]
},
{
"cell_type": "code",
"execution_count": 64,
"id": "5400e172",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1200x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"NV = dataperbandingan[dataperbandingan['model'] == 'naive_bayes']\n",
"\n",
"sns.set_style(\"whitegrid\")\n",
"plt.figure(figsize=(12, 5))\n",
"\n",
"plt.plot(NV['latih_uji'], NV['akurasi'], 'o-', markersize=4, color = '#E81416', label='Akurasi')\n",
"plt.plot(NV['latih_uji'], NV['presisi'], 'o-', markersize=4, color='#FFA500', label='Presisi')\n",
"plt.plot(NV['latih_uji'], NV['recal'], 'o-', markersize=4, color='#FAEB36', label='Recal')\n",
"plt.plot(NV['latih_uji'], NV['F1'], 'o-', markersize=4, color='#79C314', label='Skor F1')\n",
"\n",
"plt.legend()\n",
"plt.grid(alpha=0.4)\n",
"plt.title(\"Hasil Kinerja Naive Bayes untuk Rasio Data 2089:22\")\n",
"plt.xlabel('Perbandingan Data Latih dan Data Uji')\n",
"plt.xticks(rotation=30, ha='right')\n",
"plt.ylabel('Nilai Kinerja')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 65,
"id": "5a242758",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1200x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"KNN = dataperbandingan[dataperbandingan['model'] == 'k_nearest_neighbor']\n",
"\n",
"sns.set_style(\"whitegrid\")\n",
"plt.figure(figsize=(12, 5))\n",
"\n",
"plt.plot(KNN['latih_uji'], KNN['akurasi'], 'o-', markersize=4, color = '#E81416', label='Akurasi')\n",
"plt.plot(KNN['latih_uji'], KNN['presisi'], 'o-', markersize=4, color='#FFA500', label='Presisi')\n",
"plt.plot(KNN['latih_uji'], KNN['recal'], 'o-', markersize=4, color='#FAEB36', label='Recal')\n",
"plt.plot(KNN['latih_uji'], KNN['F1'], 'o-', markersize=4, color='#79C314', label='Skor F1')\n",
"\n",
"plt.legend()\n",
"plt.grid(alpha=0.4)\n",
"plt.title(\"Hasil Kinerja K-Nearest Neighbor untuk Rasio Data 2089:22\")\n",
"plt.xlabel('Perbandingan Data Latih dan Data Uji')\n",
"plt.xticks(rotation=30, ha='right')\n",
"plt.ylabel('Nilai Kinerja')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ca3aefeb",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 66,
"id": "f6156b09",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Nilai_K</th>\n",
" <th>Akurasi</th>\n",
" <th>Presisi</th>\n",
" <th>Recal</th>\n",
" <th>Skor_F1</th>\n",
" <th>Waktu_Pelatihan</th>\n",
" <th>Waktu_Pengujian</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>3</td>\n",
" <td>0.80</td>\n",
" <td>0.87</td>\n",
" <td>0.80</td>\n",
" <td>0.78</td>\n",
" <td>0.0030</td>\n",
" <td>0.0240</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>4</td>\n",
" <td>0.87</td>\n",
" <td>0.92</td>\n",
" <td>0.87</td>\n",
" <td>0.85</td>\n",
" <td>0.0027</td>\n",
" <td>0.0251</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>5</td>\n",
" <td>0.87</td>\n",
" <td>0.92</td>\n",
" <td>0.87</td>\n",
" <td>0.85</td>\n",
" <td>0.0025</td>\n",
" <td>0.0255</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>6</td>\n",
" <td>0.93</td>\n",
" <td>0.95</td>\n",
" <td>0.93</td>\n",
" <td>0.93</td>\n",
" <td>0.0020</td>\n",
" <td>0.0243</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>7</td>\n",
" <td>1.00</td>\n",
" <td>1.00</td>\n",
" <td>1.00</td>\n",
" <td>1.00</td>\n",
" <td>0.0025</td>\n",
" <td>0.0249</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>8</td>\n",
" <td>0.87</td>\n",
" <td>0.92</td>\n",
" <td>0.87</td>\n",
" <td>0.85</td>\n",
" <td>0.0032</td>\n",
" <td>0.0260</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>9</td>\n",
" <td>1.00</td>\n",
" <td>1.00</td>\n",
" <td>1.00</td>\n",
" <td>1.00</td>\n",
" <td>0.0029</td>\n",
" <td>0.0258</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Nilai_K Akurasi Presisi Recal Skor_F1 Waktu_Pelatihan Waktu_Pengujian\n",
"0 3 0.80 0.87 0.80 0.78 0.0030 0.0240\n",
"1 4 0.87 0.92 0.87 0.85 0.0027 0.0251\n",
"2 5 0.87 0.92 0.87 0.85 0.0025 0.0255\n",
"3 6 0.93 0.95 0.93 0.93 0.0020 0.0243\n",
"4 7 1.00 1.00 1.00 1.00 0.0025 0.0249\n",
"5 8 0.87 0.92 0.87 0.85 0.0032 0.0260\n",
"6 9 1.00 1.00 1.00 1.00 0.0029 0.0258"
]
},
"execution_count": 66,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"perbandinganK = pd.read_excel('dataset/perbandinganK.xlsx')\n",
"perbandinganK"
]
},
{
"cell_type": "code",
"execution_count": 67,
"id": "4d47eb79",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1200x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(12, 5))\n",
"\n",
"# Plot setiap metrik\n",
"plt.plot(perbandinganK['Nilai_K'], perbandinganK['Akurasi'], marker='o', label='Akurasi', color='blue')\n",
"plt.plot(perbandinganK['Nilai_K'], perbandinganK['Presisi'], marker='o', label='Presisi', color='brown')\n",
"plt.plot(perbandinganK['Nilai_K'], perbandinganK['Recal'], marker='o', label='Recal', color='green')\n",
"plt.plot(perbandinganK['Nilai_K'], perbandinganK['Skor_F1'], marker='o', label='Skor F1', color='red')\n",
"\n",
"# Menambahkan judul dan label sumbu\n",
"plt.title('Perbandingan Kinerja Model Berdasarkan Nilai K')\n",
"plt.xlabel('Nilai K')\n",
"plt.ylabel('Nilai Kinerja')\n",
"plt.legend()\n",
"plt.grid(True)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 68,
"id": "147ea8ca",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1200x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(12, 5))\n",
"\n",
"# Plot setiap metrik\n",
"plt.plot(perbandinganK['Nilai_K'], perbandinganK['Waktu_Pelatihan'], marker='o', label='Waktu Pelatihan', color='purple')\n",
"plt.plot(perbandinganK['Nilai_K'], perbandinganK['Waktu_Pengujian'], marker='o', label='Waktu Pengujian', color='orange')\n",
"\n",
"# Menambahkan judul dan label sumbu\n",
"plt.title('Perbandingan Kinerja Model Berdasarkan Nilai K')\n",
"plt.xlabel('Nilai K')\n",
"plt.ylabel('Nilai Kinerja')\n",
"plt.legend()\n",
"plt.grid(True)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f1c7fa90",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (tugasakhir)",
"language": "python",
"name": "myenvtugasakhir"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.5"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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