Skripsi

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

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407006958	T162854	T1628542024	Central Library (REFERENS)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1628542024

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024

Collation

viii, 234 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.707

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Prodi Sistem Komputer
Data dalam sistem-sistem komputer

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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