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

HARYANI, MARDA and Oklilas, Ahmad Fali (2025) STUDI SMART TRANSPORTATION DI KOTA PALEMBANG MENUJU SMART CITY UNTUK PREDIKSI RUTE TERBAIK MENGGUNAKAN PERBANDINGAN ALGORITMA A STAR TERHADAP GLOWWORM SWARM OPTIMIZATION. Undergraduate thesis, Sriwijaya University.

Preview	Image RAMA_56201_09011182126013_cover.jpg - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (357kB) | Preview
	Text RAMA_56201_09011182126013.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (12MB) | Request a copy
	Text RAMA_56201_09011182126013_TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (8MB) | Request a copy
	Text RAMA_56201_09011182126013_0015107201_01_front_ref.pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (1MB)
	Text RAMA_56201_09011182126013_0015107201_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (787kB) | Request a copy
	Text RAMA_56201_09011182126013_0015107201_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy
	Text RAMA_56201_09011182126013_0015107201_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (3MB) | Request a copy
	Text RAMA_56201_09011182126013_0015107201_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (279kB) | Request a copy
	Text RAMA_56201_09011182126013_0015107201_06_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (264kB) | Request a copy
	Text RAMA_56201_09011182126013_0015107201_07_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (2MB) | Request a copy

Abstract

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.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	YOLOv9, Kemacetan Lalu Lintas, A Star, Glowworm Swarm Optimization, Rute Optimal.
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:	Marda Haryani
Date Deposited:	21 May 2025 05:44
Last Modified:	21 May 2025 05:44
URI:	http://repository.unsri.ac.id/id/eprint/173459

Actions (login required)

View Item