MIF_E31222492/Pengumpulan Data/Model-Naive Bayes.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Naive Bayes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Confusion Matrix:\n",
      "[[225 187 179]\n",
      " [  4 579   8]\n",
      " [ 48  79 464]]\n",
      "\n",
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "     Negatif       0.81      0.38      0.52       591\n",
      "      Netral       0.69      0.98      0.81       591\n",
      "     Positif       0.71      0.79      0.75       591\n",
      "\n",
      "    accuracy                           0.72      1773\n",
      "   macro avg       0.74      0.72      0.69      1773\n",
      "weighted avg       0.74      0.72      0.69      1773\n",
      "\n",
      "\n",
      "Cross-Validation Scores:\n",
      "[0.68020305 0.6965595  0.6999436  0.74393683 0.76931754]\n",
      "Mean Cross-Validation Score: 0.7180\n",
      "Standard Deviation of Cross-Validation Scores: 0.0332\n"
     ]
    }
   ],
   "source": [
    "# Import library yang diperlukan\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split, cross_val_score\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.metrics import classification_report, confusion_matrix\n",
    "\n",
    "# Membaca dataset yang sudah di-balance\n",
    "df_balanced = pd.read_csv('data-analisis/datasets-balanced.csv')\n",
    "\n",
    "# Memisahkan fitur dan label\n",
    "X = df_balanced.drop(columns=['label'])  # Menghapus kolom label\n",
    "y = df_balanced['label']  # Mengambil kolom label\n",
    "\n",
    "# Membagi dataset menjadi data latih (80%) dan data uji 20%)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42, stratify=y)\n",
    "\n",
    "# Membuat model Naive Bayes\n",
    "nb_model = GaussianNB()  # Model Naive Bayes\n",
    "nb_model.fit(X_train, y_train)\n",
    "\n",
    "# Melakukan prediksi pada data uji\n",
    "y_pred = nb_model.predict(X_test)\n",
    "\n",
    "# Menampilkan hasil evaluasi\n",
    "print(\"Confusion Matrix:\")\n",
    "print(confusion_matrix(y_test, y_pred))\n",
    "print(\"\\nClassification Report:\")\n",
    "print(classification_report(y_test, y_pred))\n",
    "\n",
    "# Evaluasi model menggunakan cross-validation\n",
    "cv_scores = cross_val_score(nb_model, X, y, cv=5)  # Menggunakan 5-fold cross-validation\n",
    "\n",
    "# Menampilkan hasil cross-validation\n",
    "print(\"\\nCross-Validation Scores:\")\n",
    "print(cv_scores)\n",
    "print(f\"Mean Cross-Validation Score: {cv_scores.mean():.4f}\")\n",
    "print(f\"Standard Deviation of Cross-Validation Scores: {cv_scores.std():.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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ly2vYsGEaNWqUunXrdsvjVqxYURs2bNDhw4dVt25dPfTQQxo2bJiCg4Pv9ykDyGJ4+h4AAAAAAABMx0wpAAAAAAAAmI5QCgAAAAAAAKYjlAIAAAAAAIDpCKUAAAAAAABgOkIpAAAAAAAAmI5QCgAAAAAAAKYjlAIAAAAAAIDpCKUAAAAAAABgOkIpAAAAAAAAmI5QCgAAAAAAAKYjlAIAAAAAAIDpCKUAAAAAAABguv8Dq1cIKuHS4OoAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Generate confusion matrix\n",
    "conf_matrix = confusion_matrix(y_test, y_pred)\n",
    "\n",
    "# Visualization\n",
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "# Subplot for Confusion Matrix\n",
    "plt.subplot(1, 2, 1)\n",
    "sns.heatmap(conf_matrix, annot=True, fmt='d', cmap='Blues', cbar=False)\n",
    "plt.title('Confusion Matrix')\n",
    "plt.xlabel('Predicted')\n",
    "plt.ylabel('True')\n",
    "\n",
    "# Subplot for Cross-Validation Scores\n",
    "plt.subplot(1, 2, 2)\n",
    "sns.boxplot(data=cv_scores, orient='w')\n",
    "plt.title('Cross-Validation Scores')\n",
    "plt.xlabel('Score')\n",
    "plt.ylabel('CV Fold')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import joblib\n",
    "\n",
    "# Menampilkan hasil evaluasi\n",
    "class_report = classification_report(y_test, y_pred, output_dict=True)  # Get report as dict\n",
    "\n",
    "# Save the model\n",
    "with open('model-nb.pkl', 'wb') as file:\n",
    "    joblib.dump(nb_model, file)\n",
    "\n",
    "# Save evaluation results\n",
    "results = {\n",
    "    'Confusion Matrix': [conf_matrix.flatten()],  # Flatten for easier saving\n",
    "    'Classification Report': [class_report],\n",
    "    'Cross-Validation Scores': [cv_scores.tolist()],\n",
    "    'Mean CV Score': [cv_scores.mean()],\n",
    "    'Std Dev CV Score': [cv_scores.std()]\n",
    "}\n",
    "\n",
    "results_df = pd.DataFrame(results)\n",
    "results_df.to_csv('HASIL-RISET/evaluation_results_nb-new.csv', index=False)  # Save results to CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# export data uji\n",
    "X_test.to_csv('HASIL-RISET/X_test.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import joblib\n",
    "\n",
    "# Muat data uji\n",
    "X_test = pd.read_csv('HASIL-RISET/X_test.csv')\n",
    "\n",
    "# Muat model dari file joblib\n",
    "nb_model = joblib.load('HASIL-RISET/nb_model.pkl')\n",
    "\n",
    "# Lakukan prediksi pada data uji\n",
    "y_pred = nb_model.predict(X_test)\n",
    "\n",
    "# Ekspor hasil prediksi ke file CSV\n",
    "predictions_df = pd.DataFrame(y_pred, columns=['predicted_label'])\n",
    "predictions_df.to_csv('HASIL-RISET/y_pred_naive_bayes.csv', index=False)\n",
    "\n",
    "# Hitung jumlah prediksi untuk setiap kelas\n",
    "unique, counts = np.unique(y_pred, return_counts=True)\n",
    "sentiment_counts = dict(zip(unique, counts))\n",
    "\n",
    "# Buat pie chart\n",
    "labels = sentiment_counts.keys()\n",
    "sizes = sentiment_counts.values()\n",
    "colors = ['red', 'blue', 'green']\n",
    "# explode = (0.1, 0, 0)  # Hanya meledakkan bagian pertama (Negatif)\n",
    "\n",
    "plt.figure(figsize=(8, 8))\n",
    "plt.pie(sizes, labels=labels, colors=colors, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=140)\n",
    "plt.title('Distribusi Sentimen pada Data Uji')\n",
    "plt.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.metrics import classification_report\n",
    "\n",
    "# Mendapatkan classification report dalam bentuk dictionary\n",
    "report = classification_report(y_test, y_pred, output_dict=True)\n",
    "\n",
    "# Mengonversi ke DataFrame untuk visualisasi\n",
    "df_report = pd.DataFrame(report).T\n",
    "\n",
    "# Menghapus support karena bukan metrik evaluasi\n",
    "df_report = df_report.drop(columns=['support'])\n",
    "\n",
    "# Membuat heatmap\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.heatmap(df_report, annot=True, cmap='coolwarm', fmt='.2f', linewidths=0.5)\n",
    "plt.title(\"Classification Report Heatmap\")\n",
    "plt.ylabel(\"Classes & Averages\")\n",
    "plt.xlabel(\"Metrics\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "from sklearn.metrics import classification_report\n",
    "\n",
    "# Contoh report\n",
    "report = classification_report(y_test, y_pred, output_dict=True)\n",
    "\n",
    "# Mengonversi ke DataFrame\n",
    "df_report = pd.DataFrame(report).T\n",
    "\n",
    "# Menghapus kolom support\n",
    "df_report = df_report.drop(columns=['support'])\n",
    "\n",
    "# Membuat bar chart\n",
    "df_report.plot(kind='bar', figsize=(10, 6), colormap='coolwarm', edgecolor='black')\n",
    "plt.title(\"Distribusi Metrik Evaluasi Tiap Kelas\")\n",
    "plt.ylabel(\"Score\")\n",
    "plt.xlabel(\"Classes & Averages\")\n",
    "plt.xticks(rotation=45)\n",
    "plt.legend(title=\"Metrics\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\62851\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "c:\\Users\\62851\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "c:\\Users\\62851\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Mengubah data ke format long untuk seaborn\n",
    "df_long = df_report.reset_index().melt(id_vars=['index'], var_name='Metric', value_name='Score')\n",
    "\n",
    "# Plot boxplot\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.boxplot(x='Metric', y='Score', data=df_long, palette='coolwarm')\n",
    "plt.title(\"Distribusi Metrik Evaluasi\")\n",
    "plt.xlabel(\"Metric\")\n",
    "plt.ylabel(\"Score\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\62851\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\_oldcore.py:1498: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead\n",
      "  if pd.api.types.is_categorical_dtype(vector):\n",
      "c:\\Users\\62851\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\seaborn\\_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
      "  with pd.option_context('mode.use_inf_as_na', True):\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 6))\n",
    "sns.histplot(df_long['Score'], bins=10, kde=True, color='blue')\n",
    "plt.title(\"Histogram Distribusi Skor Metrik\")\n",
    "plt.xlabel(\"Score\")\n",
    "plt.ylabel(\"Frequency\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "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": 2
}