ANALISIS SENTIMEN TERHADAP KEMACETAN LALU LINTAS MENGGUNAKAN ALGORITMA LSTM BERDASARKAN DATA PADA MEDIA SOSIAL DAN REKAMAN CCTV DI JALAN PROTOKOL PALEMBANG

FANHARI, YOGA and Oklilas, Ahmad Fali (2025) ANALISIS SENTIMEN TERHADAP KEMACETAN LALU LINTAS MENGGUNAKAN ALGORITMA LSTM BERDASARKAN DATA PADA MEDIA SOSIAL DAN REKAMAN CCTV DI JALAN PROTOKOL PALEMBANG. Undergraduate thesis, Sriwijaya University.

Preview	Image RAMA_56201_09011382025123_Cover.jpg - Cover Image Available under License Creative Commons Public Domain Dedication. Download (1MB) | Preview
	Text RAMA_56201_09011382025123.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (3MB) | Request a copy
	Text RAMA_56201_09011382025123_TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (4MB) | Request a copy
	Text RAMA_56201_09011382025123_0015107201_01_front_ref.pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (822kB)
	Text RAMA_56201_09011382025123_0015107201_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (435kB) | Request a copy
	Text RAMA_56201_09011382025123_0015107201_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (753kB) | Request a copy
	Text RAMA_56201_09011382025123_0015107201_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy
	Text RAMA_56201_09011382025123_0015107201_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (120kB) | Request a copy
	Text RAMA_56201_09011382025123_0015107201_06_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (184kB) | Request a copy
	Text RAMA_56201_09011382025123_0015107201_07_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (720kB) | Request a copy

Abstract

This research aims to analyze public sentiment towards traffic congestion in Palembang City using the Long Short Term Memory (LSTM) algorithm and then video recording using YOLOv8 followed by LSTM. The method used includes data collection from social media platforms and videos about traffic jams, followed by analysis using object detection and sentiment classification techniques. calculation of video recordings obtained the accuracy of motorcycles by 89.31%, cars by 87.01%, three-wheeled motorcycles by 100% with the average value in the video truth table is 92.10%. The evaluation results of the LSTM algorithm work quite well in analyzing Social Media sentiment, with an accuracy rate of 75.76% on training data and 80.30% on test data, from a total of 66 lines of test data analyzed, 15 data were found that matched or matched between LSTM predictions and video recording data, resulting in an accuracy rate of 22.73%. Because the accuracy value is quite low, it is recommended to use other better methods, this research shows Social Media as an alternative source of information in monitoring traffic conditions.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	sentiment analysis, traffic jam, yolov8, long short term memory (LSTM), social media, video recording.
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:	Yoga Fanhari
Date Deposited:	11 Apr 2025 01:37
Last Modified:	11 Apr 2025 01:37
URI:	http://repository.unsri.ac.id/id/eprint/162688

Actions (login required)

View Item