Rancang Bangun Sistem Cerdas Pemantauan dan Analisis Kepadatan Lalu Lintas Berbasis Computer Vision Menggunakan Algoritma YOLOv11: Design and Development of an Intelligent Traffic Density Monitoring and Analysis System Based on Computer Vision Using the YOLOv11 Algorithm

Taufiqul Israt; Yeka Hendriyani; Mahesi Agni Zaus; Vikri Aulia

doi:10.57152/malcom.v6i4.2882

Authors

Taufiqul Israt Universitas Negeri Padang
Yeka Hendriyani Universitas Negeri Padang
Mahesi Agni Zaus Universitas Negeri Padang
Vikri Aulia Universitas Negeri Padang

DOI:

https://doi.org/10.57152/malcom.v6i4.2882

Keywords:

ByteTrack, Kepadatan Lalu Lintas, Penghitungan Kendaraan, PKJI 2023, Visi Komputer, YOLOv11

Abstract

Penelitian ini mengembangkan sistem pemantauan dan analisis lalu lintas berbasis computer vision dengan mengintegrasikan YOLOv11L, ByteTrack, polygon zone, dan counting line. Dataset terdiri atas 7.061 citra dengan empat kelas kendaraan, yaitu sepeda motor, mobil, bus, dan truk. Model dilatih selama 100 epoch menggunakan ukuran citra 640 × 640 piksel. Hasil evaluasi menunjukkan precision 0,94073, recall 0,90639, mAP50 0,96290, dan mAP50–95 0,85763. Validasi video berdurasi satu jam menghasilkan 1.983 kendaraan berdasarkan sistem dan 2.046 kendaraan berdasarkan penghitungan manual, dengan akurasi penghitungan 96,92% pada kecepatan pemrosesan 24 FPS. Berdasarkan PKJI 2023, arus lalu lintas pagi sebesar 954,10 smp/jam dengan derajat kejenuhan 0,17, sedangkan sore sebesar 1.375,80 smp/jam dengan derajat kejenuhan 0,25. Kedua nilai tersebut berada di bawah ambang 0,85, sehingga kondisi ruas jalan masih tergolong baik. Sistem juga mencatat 11 indikasi kendaraan pada zona larangan parkir pagi dan 18 indikasi sore berdasarkan posisi serta durasi berhenti minimal 30 detik dalam polygon. Hasil penelitian menunjukkan sistem mampu mengintegrasikan deteksi, pelacakan, penghitungan kendaraan, analisis derajat kejenuhan, dan pemantauan zona larangan parkir secara otomatis dalam satu sistem, sehingga memberikan informasi lalu lintas yang akurat, real-time, dan mendukung evaluasi kondisi jalan serta pengawasan parkir secara efektif dan terintegrasi bagi pengelola jalan.

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