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All Journal Journal of Applied Computer Science and Technology (JACOST)
Shendy Saputra
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Computer Science & IT

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Rancang Bangun dan Evaluasi Sistem Sortir Otomatis Barang dengan Metode Deteksi Objek YOLO v5 dan Kendali PLC Outseal Pamungkas, Daniel Sutopo; Shendy Saputra; Anastasya Andaresta Pelmelay
Journal of Applied Computer Science and Technology Vol 6 No 1 (2025): Juni 2025
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/jacost.v6i1.1165

Abstract

Manual sorting in manufacturing is time-consuming, labor-intensive, and prone to errors, especially when items have similar colors and shapes. This study aims to design and implement an automatic sorting system for goods based on color and shape to enhance production efficiency. The system integrates a webcam for image acquisition, the YOLO v5 object detection algorithm for real-time classification, and the Outseal PLC to control actuators via a Ladder Diagram. An experimental method was used, with a dataset of 18 object types tested under three lighting conditions (daylight, low light, and ring light). Performance was evaluated using a confusion matrix, achieving an average accuracy of 88.26% and precision of 70.38%, with the best results under ring light illumination. These findings demonstrate that the proposed system can reduce operational costs and improve productivity for small- to medium-scale industries. Future work should include extended field testing and adaptive algorithms for varying lighting environments.
Co-Authors Anastasya Andaresta Pelmelay Daniel Sutopo Pamungkas, Daniel Sutopo