Work

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

Year: 2024

Type: article

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.

Source: International Journal of Multilingual Education and Applied Linguistics

DOI: 10.61132/ijmeal.v1i4.148

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

Institution: IPB University

Language: English

Topic: Advanced Neural Network Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Responsible consumption and production

Open Access status: hybrid

OpenAlex ID: W4404621150

FWCI:

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