DETECTION OF MOTORBIKE RIDERS WITHOUT HELMETS ON HIGHWAYS USING YOLOV5
Kata Kunci:
Rider Detection, Helmet Use, Motorbikes, YOLOv5, Traffic Safety, Computer Vision, Road Monitoring System, Automatic Visual DetectionAbstrak
Driving safety is an important aspect in reducing traffic accident rates, especially for motorcycle riders. The use of helmets is an obligation that must be obeyed, but violations still often occur on the highway. This study aims to design and implement an automatic system for detecting motorcycle riders without helmets using the You Only Look Once version 5 (YOLOv5) algorithm. This system works by utilizing traffic images and videos as input to detect motorbike rider objects and classify helmet use. The research process includes dataset collection, data labeling, YOLOv5 model training, and system performance testing based on accuracy, precision, and recall. The research results show that the YOLOv5 algorithm is able to detect motorcycle riders without helmets with a good level of accuracy and relatively fast processing time, so this system has the potential to be applied as a real-time traffic monitoring tool to improve safety and rider compliance on the highway.Referensi
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