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A Bangkit 2023 capstone project with the theme of sustainable living by utilizing FastAPI as the backend and Android (Kotlin) as the frontend.

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MenDaur: Bangkit C23-PR537 Product Capstone Project

Hello, Everyone! We are from C23-PR537 team, consisting of 1 Mobile Development, 2 Cloud Computing, and 3 Machine Learning student. Here is our repository for MenDaur project. MenDaur is a Bangkit 2023 capstone project with the theme of sustainable living by utilizing FastAPI as the backend and Android (Kotlin) as the frontend.

Meet our team!

ID Name Learning Path
A304DSX1096 Abednego Christianyoel Rumagit Mobile Development
C172DKX4165 Anden Nirboyo Cloud Computing
C304DSX1945 Rivardi Cloud Computing
M169DSX1318 Naufal Mu’afi Machine Learning
M181DSX0325 Kelvin Erlangga Machine Learning
M151DSX2483 Arifful Fikri Machine Learning

What is MenDaur?

Mendaur is an application that can detect organic and inorganic garbage and provides recycling advice. Mendaur's advanced waste detection system helps clients choose recycling options. Mendaur recycles non-organic waste and locates convenient waste disposal locations. This tool helps users identify disposal centers, promoting waste management and lowering environmental effects.

How does this app work?

Logo    Logo    Logo    Logo   

What happened behind this app?

Try out our app!

If you want to know more about this app, you can download it here.

Important Links

Datasets

You can access our used public datasets on the following links:

  1. Garbage_classification.zip
  2. recycle_recommendation.json

API Documentation

You can access our API Documentation on the following links: Deployed API docs

UI/UX Design

You can access our prototype design on the following links: UI/UX Design

Repository (check out our each path's folder if you want to replicate our steps)

Learning Path Folder Name Folder Link
Mobile Development Mobile-Development MD Folder
Cloud Computing Cloud Computing CC Folder
Machine Learning Machine Learning ML Folder

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A Bangkit 2023 capstone project with the theme of sustainable living by utilizing FastAPI as the backend and Android (Kotlin) as the frontend.

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  • Jupyter Notebook 86.6%
  • Kotlin 10.0%
  • Python 3.4%