Sa'adat, Fadhil
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Implementasi YOLOv8 Dalam Deteksi Angka Meteran Air PDAM Sa'adat, Fadhil; Widiyanto, Eka Puji
JATISI Vol 11 No 3 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i3.9081

Abstract

The Regional Water Company (PDAM) is responsible for providing clean water and recording water consumption through meters. The current manual recording system often leads to issues such as recording errors and customer dissatisfaction. To address these problems, this study developed a system for detecting and recognizing PDAM water meter numbers using the You Only Look Once Version 8 (YOLOv8) method. YOLOv8 is an object detection method based on convolutional neural networks, capable of identifying objects in real-time with high accuracy. The aim of this study is to create a system that can automatically recognize numbers on water meters, improve recording accuracy, and reduce human errors made by meter reading officers. The research methods used include image data collection, YOLOv8 model training, and system testing. The test results show that the developed model achieved a precision of 98.1%, a recall of 97.7%, with a mean Average Precision (mAP) of 99.2%.