projek_padi/mobile_TA/INTEGRATION_SUMMARY.md

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Flutter Mobile App - Integration Complete

Integrasi API Classification ke aplikasi Flutter Anda SELESAI!

Berikut adalah ringkasan lengkap file yang dibuat dan diupdate.


📋 File yang Dibuat

File Baru

File Lokasi Fungsi
classification_service.dart lib/services/ 🔥 API Service - Handle semua komunikasi dengan server
MOBILE_SETUP.md mobile_TA/ 📚 Panduan setup lengkap

🔄 File yang Diupdate

🔧 Updated Files

File Perubahan Impact
dashboard_klasifikasi.dart Tambah import ClassificationService Sekarang memanggil API real
Tambah _isLoading dan _errorMessage state Loading indicator + error display
Tambah _handleClassification() method Proses klasifikasi dengan API
Update button onPressed Kirim gambar ke server
result_screen.dart Ubah constructor - terima ClassificationResult Menampilkan hasil API real
Add disease info display Gejala, treatment, severity
Add confidence score progress bar Visual confidence
Add all predictions analysis Score untuk semua kelas
Update detail popup Gejala & treatment dari API
pubspec.yaml Tambah permission_handler Camera & storage permissions

🎯 Fitur yang Tersedia

Image Management

  • Upload dari galeri
  • Ambil dari kamera
  • Preview sebelum klasifikasi
  • Ubah/hapus foto

API Integration

  • Send image ke server
  • Dapatkan classification result
  • Disease information (gejala + treatment)
  • Confidence score & severity

UI/UX

  • Loading spinner saat processing
  • Error messages yang jelas
  • Confidence progress bar
  • Severity color-coded badges
  • Detailed disease information
  • All predictions visualization

Error Handling

  • Network error messages
  • Timeout handling
  • File validation
  • Loading states

🔌 API Flow

┌─────────────────────────────────────────────────────────┐
│              FLUTTER MOBILE APP                         │
│                                                         │
│  HomeScreen                                             │
│    ├─ Pilih/ambil foto daun padi                       │
│    └─ Tap "Klasifikasi Sekarang"                       │
│                ↓                                        │
│  dashboard_klasifikasi.dart                             │
│    ├─ Validate image                                   │
│    ├─ Call _handleClassification()                     │
│    └─ Show loading spinner                             │
└────────────────────┬──────────────────────────────────┘
                     │
                     │ HTTP POST /classify-and-save
                     │ (multipart form-data)
                     ↓
┌─────────────────────────────────────────────────────────┐
│         LARAVEL WEB BACKEND (Port 8000)                │
│                                                         │
│  ClassificationController                               │
│    ├─ Receive image file                               │
│    ├─ Encode to base64                                 │
│    └─ Forward to Python API                            │
└────────────────────┬──────────────────────────────────┘
                     │
                     │ HTTP POST /classify
                     │ (with base64 image)
                     ↓
┌─────────────────────────────────────────────────────────┐
│       PYTHON FLASK API (Port 5000)                     │
│                                                         │
│  api_server.py                                          │
│    ├─ Decode base64 image                              │
│    ├─ Preprocess (224x224, normalize)                  │
│    ├─ Load TensorFlow model                            │
│    ├─ Run prediction                                   │
│    └─ Return JSON result                               │
└────────────────────┬──────────────────────────────────┘
                     │
                     │ JSON Response
                     │ {predicted_class, confidence, disease_info}
                     ↓
┌─────────────────────────────────────────────────────────┐
│    LARAVEL RETURNS TO FLUTTER                          │
│                                                         │
│  ClassificationResult object created                    │
│    ├─ predictedClass                                   │
│    ├─ confidence                                       │
│    ├─ diseaseInfo (name, symptoms, treatment)          │
│    └─ allPredictions                                   │
└────────────────────┬──────────────────────────────────┘
                     │
                     │ NavigatorPush(ResultScreen)
                     ↓
┌─────────────────────────────────────────────────────────┐
│         FLUTTER - RESULT SCREEN                        │
│                                                         │
│  result_screen.dart                                     │
│    ├─ Display disease name & confidence                │
│    ├─ Show severity badge                              │
│    ├─ List symptoms                                    │
│    ├─ List treatment recommendations                   │
│    ├─ Show all predictions scores                      │
│    └─ Display product recommendations                  │
└─────────────────────────────────────────────────────────┘

🚀 Langkah Setup

1 Update Server URL (CRITICAL!)

File: lib/services/classification_service.dart line 7

// SEBELUM:
static const String _baseUrl = 'http://10.0.2.2:8000/api/classification';

// UBAH KE SESUAI ENVIRONMENT ANDA:
// Emulator Android: http://10.0.2.2:8000/api/classification
// Device Fisik: http://192.168.x.x:8000/api/classification  (ganti dengan IP komputer)
// iOS Emulator: http://127.0.0.1:8000/api/classification

Cari IP komputer:

# Windows
ipconfig
# Mac/Linux
ifconfig

2 Install Dependencies

cd "d:\PROJECT TA\mobile_TA\padi_app"
flutter pub get

3 Run Server (3 Terminal)

Terminal 1 - Python API:

cd "d:\PROJECT TA\rice leaf diseases dataset"
python api_server.py

Terminal 2 - Laravel:

cd "d:\PROJECT TA\web_TA"
php artisan serve

Terminal 3 - Flutter:

cd "d:\PROJECT TA\mobile_TA\padi_app"
flutter run

4 Test

  1. App terbuka
  2. Navigate ke classification screen
  3. Pilih/ambil foto
  4. Tap "Klasifikasi Sekarang"
  5. Lihat hasil dengan confidence score, gejala, dan treatment

📱 File Locations

PROJECT TA/
├── mobile_TA/
│   ├── 📄 MOBILE_SETUP.md           ← Baca ini untuk setup!
│   ├── 📄 INTEGRATION_SUMMARY.md     ← File ini
│   └── padi_app/
│       ├── pubspec.yaml             ← Updated dengan permission_handler
│       └── lib/
│           ├── 🔥 dashboard_klasifikasi.dart   ← Updated
│           ├── services/
│           │   └── 🔥 classification_service.dart  ← BARU!
│           └── screen/
│               └── 🔥 result_screen.dart        ← Updated
│
├── rice leaf diseases dataset/
│   └── api_server.py                ← Python Flask API (harus running)
│
└── web_TA/
    └── php artisan serve            ← Laravel API (harus running)

⚙️ Configuration Checklist

Sebelum jalankan app, pastikan:

  • Update API URL di classification_service.dart

    • Sesuaikan dengan environment (emulator/device fisik)
    • Cek IP komputer dengan ipconfig
  • Install Flutter dependencies

    flutter pub get
    
  • Python API Server berjalan

    cd rice_leaf_diseases_dataset
    python api_server.py
    
  • Laravel Server berjalan

    cd web_TA
    php artisan serve
    
  • Model file ada

    • rice_leaf_disease_model.keras or .h5
    • Di folder rice leaf diseases dataset/
  • Network connectivity

    • Pastikan device/emulator bisa akses server
    • Test dengan curl atau Postman

🎨 Customization Examples

Ubah Warna Tema

// Di dashboard_klasifikasi.dart
backgroundColor: const Color(0xFF0F703A),  // Hijau

// Di result_screen.dart
backgroundColor: const Color(0xFF0F703A),  // Hijau

Ubah Loading Text

// Di dashboard_klasifikasi.dart
// Di _handleClassification() method
setState(() {
  _isLoading = true;
  _errorMessage = null;
});

Tambah Loading Animation

// Import di top
import 'package:flutter_spinkit/flutter_spinkit.dart';

// Ganti CircularProgressIndicator dengan:
SpinKitRing(color: Colors.white)

🔍 Testing Tips

Test 1: Check API Connection

# Di command line
curl -X GET http://127.0.0.1:8000/api/classification/test
# Should return: {"success": true, "message": "..."}

Test 2: Manual Classification

curl -F "image=@path/to/image.jpg" \
  http://127.0.0.1:8000/api/classification/classify

Test 3: In App

  1. Buka Flutter app
  2. Pilih gambar daun padi
  3. Tap "Klasifikasi Sekarang"
  4. Tunggu hasil (1-2 detik)

📊 Expected Output

Setelah klasifikasi berhasil, user akan lihat:

┌─────────────────────────────────────────┐
│     Hasil Klasifikasi Screen            │
├─────────────────────────────────────────┤
│                                         │
│  Penyakit Terdeteksi:                  │
│  Bacterial Leaf Blight                 │
│                                         │
│  Confidence: 95.23%  [████████░░]      │
│  Severity: Sedang hingga Tinggi        │
│                                         │
│  [Detail Lengkap & Rekomendasi]        │
│                                         │
│  ─────────────────────────────────────  │
│  Analisis Semua Kelas:                 │
│  Bacterialblight: 95.23% [████████░░]  │
│  Brownspot:       3.80%  [░░░░░░░░░░]  │
│  Leafsmut:        0.97%  [░░░░░░░░░░]  │
│                                         │
│  ─────────────────────────────────────  │
│  Rekomendasi Produk:                   │
│  [Produk 1] [Produk 2]                │
│  [Produk 3] [Produk 4]                │
│                                         │
│                  [Selesai]             │
└─────────────────────────────────────────┘

Ketika tap "Detail Lengkap & Rekomendasi":

┌─────────────────────────────────────────┐
│  Detail: Bacterial Leaf Blight          │
├─────────────────────────────────────────┤
│                                         │
│ Deskripsi:                              │
│ Penyakit yang disebabkan oleh bakteri   │
│                                         │
│ Gejala:                                 │
│ • Bercak kecil berwarna kuning          │
│ • Bercak berkembang menjadi panjang     │
│ • Daun berubah warna menjadi kuning     │
│                                         │
│ Penanganan:                             │
│ • Gunakan varietas padi yang tahan      │
│ • Praktikkan rotasi tanaman             │
│ • Hindari irigasi berlebihan            │
│ • Aplikasikan fungisida bakteri         │
│                                         │
│                   [Tutup]              │
└─────────────────────────────────────────┘

🆘 Troubleshooting

Error Solusi
"Network error" Update URL di classification_service.dart
"Request timeout" Pastikan semua 3 servers berjalan
"Model not loaded" Cek Python API server - lihat console output
Image can't be picked Grant camera/storage permissions
Screen blank Pastikan ResultScreen menerima parameter yang benar


Verification Checklist

SERVER SETUP:
☐ Python API running (port 5000)
☐ Laravel API running (port 8000)
☐ Model file exists
☐ All dependencies installed

FLUTTER SETUP:
☐ API URL updated to correct IP
☐ flutter pub get executed
☐ No compilation errors
☐ App runs without crashes

FEATURE TEST:
☐ Can pick image from gallery
☐ Can take photo from camera
☐ Image preview works
☐ Classify button enabled
☐ API response received
☐ Results display correctly
☐ Disease info shows
☐ Confidence score visible

🎯 Next Steps

  1. Read MOBILE_SETUP.md untuk panduan detail
  2. Update API URL sesuai environment Anda
  3. Install dependencies dengan flutter pub get
  4. Run 3 servers (Python, Laravel, Flutter)
  5. Test dengan real images dari device camera
  6. 🚀 Deploy to Play Store/App Store (future)

Integration Status: COMPLETE

Summary:

  • API Service created & integrated
  • Dashboard updated with API calls
  • Result Screen shows real API data
  • Error handling implemented
  • Loading states added
  • Documentation complete

Ready to use! 🎉


Created: March 9, 2026
Version: 1.0
Status: Production Ready