OPTIMASI LALU LINTAS KOTA PALEMBANG : ANALISA KEPADATAN KENDARAAN MENGGUNAKAN ALGORITMA NAÏVE BAYES DAN PENENTUAN JALUR TERBAIK MENGGUNAKAN ALGORITMA WEIGHTED A*

NUR'ALIM, MUHAMMAD IQBAL and Oklilas, Ahmad Fali (2024) OPTIMASI LALU LINTAS KOTA PALEMBANG : ANALISA KEPADATAN KENDARAAN MENGGUNAKAN ALGORITMA NAÏVE BAYES DAN PENENTUAN JALUR TERBAIK MENGGUNAKAN ALGORITMA WEIGHTED A*. Undergraduate thesis, Sriwijaya University.

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Abstract

Traffic congestion in Palembang City is a major problem, especially during rush hour, which impacts travel efficiency and increases vehicle emissions. Traffic management that is not yet optimal in utilizing intelligent technology makes it difficult to handle dynamic conditions. This study aims to analyze and manage traffic in Palembang City with three methods: vehicle detection using YOLOv8, traffic density prediction with the Naïve Bayes algorithm, and determining the best path using the Weighted A* algorithm. The results show that YOLOv8 has an accuracy of 82.6% on training data, 82.49% on testing data, and 82.49% on validation data. The CCTV-based implementation shows a vehicle detection accuracy of 93.65%. The Naïve Bayes algorithm shows a model accuracy of 87.16% and an average prediction accuracy of 96.96% in the six time conditions tested. The Weighted A* algorithm is able to dynamically select the best path, avoiding congestion even though the distance is further. The combination of these three methods shows potential as an adaptive and efficient solution for traffic management in Palembang City.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	YOLOv8, naïve bayes , weighted a*, kepadatan kendaraan, lalu lintas, jalur terbaik, kota palembang
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General) T Technology > TE Highway engineering. Roads and pavements > TE1-450 Highway engineering. Roads and pavements T Technology > TE Highway engineering. Roads and pavements > TE175-176.5 Highway design. Interchanges and intersections
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Muhammad Iqbal Nur’alim
Date Deposited:	07 Jan 2025 06:36
Last Modified:	07 Jan 2025 06:36
URI:	http://repository.unsri.ac.id/id/eprint/162854

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