DETEKSI KEPADATAN KENDARAAN DENGAN PERBANDINGAN ANALISA DATA MEDIA SOSIAL DAN ELCTRONIC TRAFFIC LAW ENFORCEMENT (ETLE) DIRLANTAS POLDA SUMSEL MENGGUNAKAN METODE K-NEAREST NEIGHBOR (K-NN)

SARI, TIARA MUTIA and Oklilas, Ahmad Fali (2025) DETEKSI KEPADATAN KENDARAAN DENGAN PERBANDINGAN ANALISA DATA MEDIA SOSIAL DAN ELCTRONIC TRAFFIC LAW ENFORCEMENT (ETLE) DIRLANTAS POLDA SUMSEL MENGGUNAKAN METODE K-NEAREST NEIGHBOR (K-NN). Undergraduate thesis, Sriwijaya University.

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Abstract

This study aims to compare data from two different sources, namely social media data and data from the Electronic Traffic Law Enforcement (ETLE) system, using the K-Nearest Neighbor method, in terms of the similarity between the actual labels and predicted results. The findings indicate that the similarity between the actual labels and predicted results for social media data reached 87.69%, while the similarity between social media data and ETLE data was 66.92%. This study provides insights into the potential use of social media data as an additional tool for analyzing road user behavior.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	K-Nearest Neighbor, Instagram social media, vehicle density
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:	Tiara Mutia Sari
Date Deposited:	25 Jun 2025 01:28
Last Modified:	25 Jun 2025 01:28
URI:	http://repository.unsri.ac.id/id/eprint/164420

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