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PERBANDINGAN ALGORITMA GENETIK TERHADAP PARTICLE SWARM OPTIMIZATION DALAM MENENTUKAN RUTE TERBAIK PADA SISTEM TRANSPORTASI DI JALAN RAYA KOTA PALEMBANG

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Penilaian

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This research focuses on identifying the optimal route by analyzing the results of Genetic Algorithm and Particle Swarm Optimization. This research uses You Only Look Once version 9 (YOLOv9) to create a vehicle detection and counting system using CCTV footage, with the results of Average Precision (mAP) values of 84.4% during training and 83.9% during testing. Furthermore, this study used the Decision Tree output from previous research to categorize road conditions as smooth, moderate, or congested through various parameters, including the number of vehicles, road width, and travel distance. In estimating road congestion, the Decision Tree produced a model accuracy of 92%. Next, Genetic and Particle Swarm Optimization algorithms were used to determine the best route based on travel distance and road conditions. The analysis showed that route 4 was frequently selected in various scenarios due to its minimal weight. Route 3 emerged as the preferred option on Wednesday afternoons, Saturday afternoons and evenings, while route 1 was preferred on Friday and Saturday mornings due to its shorter distance. However, route 1 was not consistently the top choice as it crosses the intersection of Charitas and Polda which often experiences congestion. A comparison between Particle Swarm Optimization and Genetic Algorithm shows that both produce almost the same routes and weights, although Particle Swarm Optimization runs faster with an average time difference of 0.0420 seconds.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507002867	T173469	T1734692025	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1734692025

Publisher

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

Collation

xiv, 76 hlm.; ill.; 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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