Implementasi Metode YOLO pada Deteksi Pakaian Keselamatan yang Lengkap di Proyek Kontruksi

Abstract

Safety at work is important, so the use of personal protective equipment (ADP) is a must. However, in reality on the ground, there are relatively few workers who use complete and correct PPE. Due to this problem, the company as the person responsible employs K3 officers to monitor workers' use of PPE. To reduce the costs incurred in employing K3 officers, a system was created that was able to detect and monitor worker discipline in using PPE. Therefore, a personal protective equipment detection system was created. One method created to create object detection is the You Only Look Once (YOLO) method. The way YOLO works is by looking at the entire image once, then passing through the neural network once to directly detect existing objects. The results of this implementation aim to detect project workers who use complete protective equipment and do not use it, with the output results in the form of images that have been detected by people who use complete protective equipment or do not use it with labeling and bounding boxes on the detected image. From the test results on a total of 96 images, it shows that there is an accuracy value of 65%.