Authors:

Kadek Adi Priana, Anak Agung Istri Ngurah Eka Karyawati

Abstract:

“At present, people’s daily garbage is increasing day by day. How to intelligently classify garbage can save manpower and improve work efficiency. In this paper, a garbage classification model is based on. First, according to the common daily garbage category, twelve typical kinds of garbage were selected, data cleaned, labeled, and constructed a garbage dataset. Second, YOLO was built and trained on our datasets. The experimental results show that YOLO can accurately identify the garbage’s types and find out the location of garbage. Keywords: YOLO, Convolutional Neural Network, Sampah, object detection”

Keywords

YOLO, Convolutional Neural Network, Sampah, object detection

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PDF:

https://jurnal.harianregional.com/jnatia/full-102970

Published

2023-11-03

How To Cite

PRIANA, Kadek Adi; EKA KARYAWATI, Anak Agung Istri Ngurah. Sistem Pendeteksi Sampah Secara Realtime Menggunakan Metode YOLO.Jurnal Nasional Teknologi Informasi dan Aplikasnya, [S.l.], v. 2, n. 1, p. 31-36, nov. 2023. ISSN 3032-1948. Available at: https://jurnal.harianregional.com/jnatia/id-102970. Date accessed: 28 Aug. 2025.

Citation Format

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Issue

Vol 2 No 1 (2023): JNATIA Vol. 2, No. 1, November 2023

Section

Articles

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License