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STUDI SMART TRANSPORTATION DI KOTA PALEMBANG MENUJU SMART CITY UNTUK PREDIKSI RUTE TERBAIK MENGGUNAKAN PERBANDINGAN ALGORITMA A STAR TERHADAP GLOWWORM SWARM OPTIMIZATION

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Penilaian

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Traffic congestion in Palembang City is caused by the number of vehicles exceeding the road capacity. This study discusses the determination of the best route in an intelligent transportation system using the A Star algorithm and Glowworm Swarm Optimization (GSO). The parameters used to compare A Star and GSO algorithms are based on path weight and execution time. YOLOv9 is used to detect and count the number of vehicles. The results show that 100 epochs were selected as the best model with mAP values of 84.4% for training, 84.3% for validation, and 83.9% for testing. Furthermore, based on previous research using LSTM, traffic density conditions were determined with outputs categorized as smooth, moderate, and congested. Finally, for route optimization, the results from A Star and GSO indicate that Route 4 was optimal on Monday and Wednesday, Route 6 on Friday, and for Saturday, the optimal routes varied: Route 6 in the morning, Route 4 at noon, and Route 1 in the evening. Regarding execution time, A Star averaged 0.00009 seconds (9 microseconds), while GSO required approximately 0.18 seconds, showing that A Star is faster in execution time. The best travel times occurred on Saturday morning and Friday afternoon, while Monday afternoon experienced the highest congestion levels.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507002863	T173459	T1734592025	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1734592025

Publisher

: Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xv, 78 hlm.: Ilus., tab.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

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Media Type

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Carrier Type

-

Edition

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Subject(s)

Ilmu Komputer

Specific Detail Info

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Statement of Responsibility

EM

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