DaurinPoin application is a waste recycling application that provides incentives to users. The app allows users to filter their waste with their phone's camera and determine its type and point value. Users can also send and deliver their waste to designated places and earn points that can be exchanged for vouchers, coupons, or donations. This application aims to help the community manage waste responsibly and sustainably.
| Member | Student ID | Path | University |
|---|---|---|---|
| Liza | M010BSX1764 | Machine Learning | Universitas Indonesia |
| Sean Edbert Thio | M102BSY0481 | Machine Learning | Institut Bisnis dan Informatika Kwik Kian Gie |
| Shahnaz Izzati Frishila | M008BSX0090 | Machine Learning | Universitas Gadjah Mada |
| Asty Yuliani | C120BSX4197 | Cloud Computing | Institut Teknologi Telkom Purwokerto |
| Delwa Diraja | C008BSY3041 | Cloud Computing | Universitas Gadjah Mada |
| Almas Fa’iq Khairul Ikhwan | A120BSY2376 | Mobile Development | Institut Teknologi Telkom Purwokerto |
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Machine Learning:
- Python
- TensorFlow
- Google Colab
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Mobile Development:
- Figma
- Android Studio
- Kotlin
- Google Maps
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Cloud Computing:
- Google Cloud Run
- Cloud SQL
- Docker
- Express.js
- Cloud Storage
Our application architecture is designed to operate in the us-central1 region, utilizing Google Cloud services. The Android client initiates requests to Cloud Run services, which act as the backend, handling API requests and responses. Cloud Run interacts with Cloud SQL for data storage and retrieval, Cloud Storage for image storage, and Cloud Build for managing the build process. This region-specific implementation ensures low latency and optimal performance, catering to users in the us-central1 region while leveraging the scalability and reliability of Google Cloud Platform.
In our project is divided into four branches:
| Nama | |
|---|---|
| Liza | |
| Sean Edbert Thio | |
| Shahnaz Izzati Frishila | |
| Asty Yuliani | |
| Delwa Diraja | |
| Almas Fa’iq Khairul Ikhwan |