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All Journal Populer: Jurnal Penelitian Mahasiswa
Tiza Farhani Maulia
Univeritas Islam Sultan Agung
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Identifikasi Pelanggaran Lalu Lintas Kendaraan Mobil terhadap Larangan Putar Balik menggunakan Algoritma You Only Look Once (YOLOv11) Tiza Farhani Maulia; Dedy Kurniadi; Ghufron Ghufron
Populer: Jurnal Penelitian Mahasiswa Vol. 5 No. 3 (2026): September : Populer: Jurnal Penelitian Mahasiswa
Publisher : Universitas Maritim AMNI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58192/populer.v5i3.5487

Abstract

The purpose of this study is to identify and analyze traffic violations involving cars that violate U-Turn prohibitions using the You Only Look Once (YOLOv11) algorithm. Illegal U-Turns in restricted areas are a primary cause of traffic congestion and accidents. This study develops an automated, real-time U-Turn violation monitoring system by integrating the YOLOv11n model, ByteTrack tracking algorithm, and Streamlit interface using 2-zone polygon logic. The dataset covers 7 vehicle classes evaluated on 1,072 validation images. Experimental results show that the YOLOv11n model achieves a mean Average Precision (mAP@50) of 66.5%, Precision of 68.4%, and Recall of 64.2%. With an inference speed of 3.2 ms per frame (169 FPS), the 2-zone logic integrated into Streamlit accurately detects illegal maneuvers, updates real-time metrics, and minimizes false alarms without frame lag. The proposed system demonstrates the potential of combining object detection, vehicle tracking, and zone-based logic for automated monitoring of U-Turn violations in restricted areas.
Co-Authors Dedy Kurniadi Ghufron Ghufron