Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
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All Journal International Journal of Multilingual Education and Applied Linguistics
Bima Julian Mahardika
Unknown Affiliation
Arts Computer Science & IT Education Languange, Linguistic, Communication & Media Public Health Social Sciences

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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
International Journal of Multilingual Education and Applied Linguistics Vol. 1 No. 4 (2024): November : International Journal of Multilingual Education and Applied Linguist
Publisher : Asosiasi Periset Bahasa Sastra Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/ijmeal.v1i4.148

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.
Co-Authors Anatasya Wenita Putri Aulia Anggraeni Budy Santoso Endang Purnama Giri Gema Parasti Mindara Muhamad Ali Imron