DETEKSI PELANGGARAN DAN KECEPATAN KENDARAAN MENGGUNAKAN YOLO DAN ALGORITMA DEEPSORT PADA REKAMAN VIDEO DI JALAN PROTOKOL DI KOTA PALEMBANG

ASSIDIQIE, MUHAMMAD FADHAM IMAM and Oklilas, Ahmad Fali (2024) DETEKSI PELANGGARAN DAN KECEPATAN KENDARAAN MENGGUNAKAN YOLO DAN ALGORITMA DEEPSORT PADA REKAMAN VIDEO DI JALAN PROTOKOL DI KOTA PALEMBANG. Undergraduate thesis, Sriwijaya University.

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Abstract

The purpose of this research is to create a detection system for violations of not using helmets and speed limit violations at several road points in Palembang City. This research uses YOLOv8 combined with Deepsort to detect the number of vehicles, especially the class of motorcycles not using helmets and speed detection. As a result, the accuracy of detection of violations not using helmets reached 89.69% and for speed violations had a MAPE (Mean Absolute Percentage Error) value of 12%. The category of violation level is predicted using KNN by dividing low, medium, and high violation levels. The results of category prediction using KNN have an accuracy rate of 89.6% by comparing the prediction results and manual calculations.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Deteksi Pelanggaran Helm, Deteksi Pelanggaran Kecepatan, YOLOv8, Deepsort, Prediksi Kategori Tingkat Pelanggaran, Metode K-NN.
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:	Muhammad Fadham Imam Assidiqie
Date Deposited:	19 Jul 2024 07:03
Last Modified:	19 Jul 2024 07:03
URI:	http://repository.unsri.ac.id/id/eprint/152056

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