174 lines
4.1 KiB
Markdown
174 lines
4.1 KiB
Markdown
# Amori AI
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Aplikasi rekomendasi menu kafe Amor Coffee Kediri menggunakan AI dan OCR technology.
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## 🚀 Fitur Utama
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- **OCR Menu Recognition**: Scan foto menu menggunakan Google Vision OCR
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- **AI-Powered Recommendations**: Rekomendasi personal menggunakan Gemini AI
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- **User Preferences**: Sistem preferensi pengguna yang komprehensif
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- **Firebase Integration**: Autentikasi dan database real-time
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- **Chat Interface**: Tanya jawab dengan AI tentang menu
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- **History & Favorites**: Riwayat rekomendasi dan favorit
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- **Offline Support**: Cache data untuk penggunaan offline
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## 🛠️ Tech Stack
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- **Framework**: Flutter 3.8.1+
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- **State Management**: Riverpod
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- **Database**: Firebase Firestore + Hive (local)
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- **Authentication**: Firebase Auth + Google Sign-In
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- **AI/ML**: Google Gemini AI + Google ML Kit OCR
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- **UI**: Material Design 3 dengan custom theme
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## 🔧 Setup & Installation
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### Prerequisites
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1. Flutter SDK 3.8.1 atau lebih baru
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2. Dart SDK
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3. Android Studio / VS Code
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4. Firebase account
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5. Google Cloud account (untuk Gemini AI)
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### Environment Variables
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Buat file `.env` di root project:
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```env
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GEMINI_API_KEY=your_gemini_api_key_here
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GOOGLE_SIGN_IN_CLIENT_ID=your_google_client_id_here
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```
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### Firebase Setup
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1. Buat project baru di [Firebase Console](https://console.firebase.google.com)
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2. Enable Authentication (Email/Password & Google)
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3. Enable Firestore Database
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4. Enable Firebase Messaging
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5. Download `google-services.json` dan letakkan di `android/app/`
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6. Download `GoogleService-Info.plist` dan letakkan di `ios/Runner/`
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### Installation Steps
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1. Clone repository:
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```bash
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git clone https://github.com/your-username/muning-menu-recommender.git
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cd muning-menu-recommender
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```
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2. Install dependencies:
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```bash
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flutter pub get
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```
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3. Generate Hive adapters:
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```bash
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flutter packages pub run build_runner build
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```
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4. Run the app:
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```bash
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flutter run
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```
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## 🏗️ Architecture
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```
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lib/
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├── core/
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│ ├── config/ # App configuration
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│ ├── constants/ # App constants
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│ └── theme/ # App theme & styling
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├── models/ # Data models
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├── services/ # Business logic services
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├── screens/ # UI screens
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│ ├── auth/ # Authentication screens
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│ ├── home/ # Home screen
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│ ├── camera/ # Camera & OCR screens
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│ ├── recommendation/ # Recommendation screens
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│ ├── history/ # History screens
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│ └── profile/ # Profile screens
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└── main.dart # App entry point
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```
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## 🧪 Testing
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### Unit Tests
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```bash
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flutter test
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```
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### Integration Tests
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```bash
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flutter drive --target=test_driver/app.dart
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```
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### Testing Strategy
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- **Black Box Testing**: Equivalence Class Partitioning (ECP), Boundary Value Analysis (BVA), Decision Table
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- **SUS Questionnaire**: System Usability Scale integration
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- **Performance Testing**: CPU usage (target: 20-36%), FPS (target: 66+)
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## 📊 Performance Metrics
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- **Target CPU Usage**: 20-36%
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- **Target FPS**: 66+
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- **OCR Accuracy**: >90%
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- **AI Response Time**: <3 seconds
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- **App Launch Time**: <2 seconds
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## 🔒 Security & Privacy
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- Data encryption in transit dan at rest
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- GDPR compliance untuk data handling
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- Secure API key management
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- User consent untuk data collection
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## 🚀 Deployment
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### Android APK
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```bash
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flutter build apk --release
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```
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### Android App Bundle
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```bash
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flutter build appbundle --release
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```
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### iOS
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```bash
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flutter build ios --release
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```
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## 🤝 Contributing
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1. Fork the project
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2. Create feature branch (`git checkout -b feature/AmazingFeature`)
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3. Commit changes (`git commit -m 'Add some AmazingFeature'`)
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4. Push to branch (`git push origin feature/AmazingFeature`)
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5. Open Pull Request
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## 📝 License
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This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
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## 👥 Team
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- **Developer**: [Your Name]
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- **UI/UX Designer**: [Designer Name]
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- **Project Manager**: [PM Name]
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## 🙏 Acknowledgments
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- Google untuk ML Kit dan Gemini AI
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- Firebase untuk backend services
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- Flutter team untuk framework yang amazing
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---
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