Abstract

The increasing amount of waste in society, especially waste mixed with organic and non-organic. This research aims to develop an effective classification system to assist waste management. The model used is DenseNet201 which is applied in image processing to classify types of waste. The data used consists of 4,752 images which are divided into two, namely organic waste having 1,808 images and non-organic waste having 2,944 images. The DenseNet201 model was trained for 50 steps and achieved 99% accuracy. The results show that this classification system is effective in differentiating waste, contributing to environmental conservation and increasing public awareness about waste separation.