diff --git a/app/Http/Controllers/DiagnosisController.php b/app/Http/Controllers/DiagnosisController.php
index b387b3a..97dfd29 100644
--- a/app/Http/Controllers/DiagnosisController.php
+++ b/app/Http/Controllers/DiagnosisController.php
@@ -8,46 +8,60 @@
class DiagnosisController extends Controller
{
public function prosesDiagnosis(Request $request)
-{
- $input = $request->input('gejala', []);
+ {
+ $input = $request->input('gejala', []);
- if (count($input) < 3) {
- return redirect()->route('gejala')
- ->with('error', 'Pilih minimal 3 gejala!');
+ // validasi minimal 3 gejala
+ if (count($input) < 3) {
+ return redirect()->route('gejala')
+ ->with('error', 'Pilih minimal 3 gejala!');
+ }
+
+ $inputNama = $input;
+
+ // ambil fitur dari Python
+ $response = Http::get('http://127.0.0.1:5000/gejala');
+
+ if (!$response->successful()) {
+ return redirect()->route('gejala')
+ ->with('error', 'Tidak bisa mengambil data gejala dari API');
+ }
+
+ $featureCols = $response->json();
+
+ // ubah ke format 1/0
+ $fiturAssoc = [];
+
+ foreach ($featureCols as $col) {
+ $fiturAssoc[$col] = in_array(trim($col), array_map('trim', $inputNama)) ? 1 : 0;
+ }
+
+ // kirim ke Python API
+ $response = Http::post('http://127.0.0.1:5000/predict', $fiturAssoc);
+
+ if (!$response->successful()) {
+ return redirect()->route('gejala')
+ ->with('error', 'Server AI tidak merespon!');
+ }
+
+ $data = $response->json();
+
+ // 🔥 ambil semua hasil dari Python
+ $diagnosis = [
+ 'nama' => $data['penyakit'] ?? '-',
+ 'kategori' => $data['jenis'] ?? '-',
+ 'pertolongan' => $data['pertolongan'] ?? [],
+ 'pencegahan' => $data['pencegahan'] ?? [],
+ ];
+
+ return redirect()->route('hasil-diagnosis')
+ ->with('diagnosis', $diagnosis)
+ ->with('gejala', $inputNama);
}
- // 🔥 LANGSUNG PAKAI INPUT
- $inputNama = $input;
-
- // ambil feature dari Python
- $response = Http::get('http://127.0.0.1:5000/gejala');
- if (!$response->successful()) {
- return redirect()->route('gejala')
- ->with('error', 'Tidak bisa mengambil data gejala dari API');
+ // 🔥 halaman hasil
+ public function hasil()
+ {
+ return view('hasil-diagnosis');
}
-
- $featureCols = $response->json();
-
- // bikin vector
- $fiturAssoc = [];
-
- foreach ($featureCols as $col) {
- $fiturAssoc[$col] = in_array(trim($col), array_map('trim', $inputNama)) ? 1 : 0;
- }
-
- // kirim ke Flask
- $response = Http::post('http://127.0.0.1:5000/predict', $fiturAssoc);
-
- if (!$response->successful()) {
- return redirect()->route('gejala')
- ->with('error', 'Server AI tidak merespon!');
- }
-
- $data = $response->json();
-
- $hasil = isset($data['hasil']) ? trim($data['hasil']) : 'Tidak diketahui';
-
- return redirect()->route('hasil-diagnosis')
- ->with('hasil', $hasil)
- ->with('gejala', $inputNama);
-}}
\ No newline at end of file
+}
\ No newline at end of file
diff --git a/public/data/Bissmilah lagi.xlsx b/public/data/Bissmilah lagi.xlsx
new file mode 100644
index 0000000..13884dc
Binary files /dev/null and b/public/data/Bissmilah lagi.xlsx differ
diff --git a/python_api/app.py b/python_api/app.py
index 9aac554..948f2a3 100644
--- a/python_api/app.py
+++ b/python_api/app.py
@@ -5,19 +5,52 @@ import pandas as pd
app = Flask(__name__)
-# load model
-model = joblib.load("../python_artifacts/modell.joblib")
+# =========================
+# LOAD MODEL
+# =========================
+model = joblib.load("../python_artifacts/model.joblib")
-# load fitur
+# =========================
+# LOAD FEATURE
+# =========================
with open("../python_artifacts/feature_cols.json") as f:
feature_cols = json.load(f)
-# endpoint gejala
+# =========================
+# LOAD EXCEL
+# =========================
+df_info = pd.read_excel("../public/data/Bissmilah lagi.xlsx")
+
+# bersihin data
+df_info.columns = df_info.columns.str.strip()
+
+for col in df_info.columns:
+ df_info[col] = df_info[col].astype(str).str.strip()
+
+df_info['Penyakit'] = df_info['Penyakit'].str.lower()
+
+# buat dictionary
+info_penyakit = {}
+
+for _, row in df_info.iterrows():
+ info_penyakit[row['Penyakit']] = {
+ "jenis": row['Jenis'],
+ "pertolongan": [p.strip() for p in row['Pertolongan'].split(";")],
+ "pencegahan": [p.strip() for p in row['Pencegahan'].split(";")]
+ }
+
+print("DATA PENYAKIT:", info_penyakit.keys())
+
+# =========================
+# ENDPOINT GEJALA
+# =========================
@app.route('/gejala', methods=['GET'])
def get_gejala():
return jsonify(feature_cols)
-# endpoint predict
+# =========================
+# ENDPOINT PREDICT
+# =========================
@app.route('/predict', methods=['POST'])
def predict():
data = request.json
@@ -35,13 +68,31 @@ def predict():
input_df = pd.DataFrame([input_data], columns=feature_cols)
hasil = model.predict(input_df)[0]
+ penyakit = str(hasil).lower().strip()
+
+ print("HASIL MODEL:", hasil)
+ print("CARI DI EXCEL:", penyakit)
+
+ info = info_penyakit.get(penyakit)
+
+ if not info:
+ return jsonify({
+ "penyakit": hasil,
+ "jenis": "-",
+ "pertolongan": [],
+ "pencegahan": []
+ })
return jsonify({
- "hasil": hasil
+ "penyakit": hasil,
+ "jenis": info["jenis"],
+ "pertolongan": info["pertolongan"],
+ "pencegahan": info["pencegahan"]
})
+
+# =========================
+# RUN APP
+# =========================
if __name__ == '__main__':
- print("API MODEL SIAP DIGUNAKAN (DARI JUPYTER)")
- app.run(debug=True)
- print("FEATURE COLS:", feature_cols)
-print("INPUT FROM LARAVEL:", data)
-print("INPUT VECTOR:", input_data)
\ No newline at end of file
+ print("API MODEL SIAP DIGUNAKAN 🔥")
+ app.run(debug=True)
\ No newline at end of file
diff --git a/python_artifacts/model.joblib b/python_artifacts/model.joblib
index 8d37fc4..41e71e2 100644
Binary files a/python_artifacts/model.joblib and b/python_artifacts/model.joblib differ
diff --git a/resources/views/hasil-diagnosis.blade.php b/resources/views/hasil-diagnosis.blade.php
index 80defa7..cedc0b4 100644
--- a/resources/views/hasil-diagnosis.blade.php
+++ b/resources/views/hasil-diagnosis.blade.php
@@ -5,7 +5,9 @@
Hasil Diagnosis - PawMedic
-
+@php
+$diagnosis = session('diagnosis')?? [];
+@endphp