PEMANTAUAN POLA PERILAKU LALU LINTAS BERBASIS JARINGAN CCTV BERDASARKAN TEKNOLOGI ANALISIS DATA MENGGUNAKAN YOLOV8 DENGAN ALGORITMA HIERARCHICAL CLUSTERING

SITEPU, HESTY NOVIA BR SITEPU and Sukemi, Sukemi and Oklilas, Ahmad Fali (2025) PEMANTAUAN POLA PERILAKU LALU LINTAS BERBASIS JARINGAN CCTV BERDASARKAN TEKNOLOGI ANALISIS DATA MENGGUNAKAN YOLOV8 DENGAN ALGORITMA HIERARCHICAL CLUSTERING. Undergraduate thesis, Sriwijaya University.

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Abstract

This study presents the design of a traffic behavior monitoring system based on CCTV networks by comparing two algorithmic approaches: YOLOv8 for real-time object detection and Hierarchical Clustering for unsupervised object grouping without prior labeling. The system is developed to automatically identify behavioral patterns in traffic, such as violations involving riders not wearing helmets. Image and video data were collected from several strategic locations in Palembang and processed through stages of annotation, model training, and performance evaluation. The YOLOv8 model demonstrated high accuracy based on evaluation metrics including confusion matrix, precision, recall, and F1-score. Meanwhile, the Hierarchical Clustering results were visualized through dendrograms, serving as a comparative reference to the YOLOv8-based classification. The findings indicate that integrating both supervised and unsupervised methods offers complementary insights and can serve as a foundation for developing more robust, data-driven traffic surveillance systems.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Pemantauan lalu lintas,YOLOv8,Hierarchical Clustering,Deteksi Pelanggaran,CCTV,Kota Palembang
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Hesty Novia Br Sitepu
Date Deposited:	31 Jul 2025 03:16
Last Modified:	31 Jul 2025 03:16
URI:	http://repository.unsri.ac.id/id/eprint/181844

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