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Deteksi Pelanggaran Kendaraan Jalur Transjakarta Menggunakan Algoritma You Only Look Once (YOLOv11)
Deteksi Pelanggaran Kendaraan Jalur Transjakarta Menggunakan Algoritma You Only Look Once (YOLOv11) Studi Kasus Halte Mangga Besar, Jakarta Fauzan Dzaki Andrian1 , 1 Program Studi Ilmu Komputer, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Pakuan, Bogor, Jawa Barat, 16143, Indonesia Abstract Vehicle violations in Transjakarta dedicated lanes disrupt the efficiency of public transportation in Jakarta. This study aims to develop an automatic detection system using the YOLOv11 algorithm to identify two-wheeled and four-wheeled vehicles violating these lanes. Data was collected through 3- minute videos in the morning, afternoon, and evening, then processed into a labeled dataset using Roboflow. The model was trained and tested using Google Collaboratory with evaluation metrics such as precision, recall, F1-score, and mAP. The best results were obtained in the afternoon with mAP@50 reaching 94.3% and precision 91.6%. YOLOv11 has proven effective in detecting violations in real-time and can be used as a tool to assist traffic law enforcement. Keywords: YOLO V11 1; Object detectiom 2; Traffic Violations 3; Transjakarta 4; Computer Vision
Fakultas Matematika dan Pengetahuan Alam, Universitas Pakuan
Fakultas Matematika dan Ilmu Pnegetahuan Alam
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