Traspoter Application Development: Website-Based Automatic Garbage Classification Using CNN Method

Bima Julian Mahardika; Budy Santoso; Aulia Anggraeni; Muhamad Ali Imron; Anatasya Wenita Putri; Endang Purnama Giri; Gema Parasti Mindara

doi:10.61132/ijmeal.v1i4.148

Authors

Bima Julian Mahardika IPB University
Budy Santoso IPB University
Aulia Anggraeni IPB University
Muhamad Ali Imron IPB University
Anatasya Wenita Putri IPB University
Endang Purnama Giri IPB University
Gema Parasti Mindara IPB University

DOI:

https://doi.org/10.61132/ijmeal.v1i4.148

Keywords:

Automatic Garbage Classification, Recycling, CNN, Python, OpenCV

Abstract

This research focuses on the development of automatic waste classification by applying the Convolutional Neural Network (CNN) method in a web-based application. This system is designed to help the waste management process through automatic sorting between organic and inorganic waste, so that it can support recycling efforts and reduce environmental impacts. In its application, this application utilizes the CNN algorithm to analyze images and recognize the type of waste with good accuracy. The development uses technologies such as Python and OpenCV to ensure efficient processing of image data, with the CNN model trained using a dataset of 22,564 images. Test results show excellent accuracy, reaching 99.27% for organic waste and 98.72% for inorganic waste.

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