JURNAL MEDIA INFORMATIKA BUDIDARMA
Vol 8, No 2 (2024): April 2024

Implementasi Metode Naive Bayes Classifier Terhadap Klasifikasi Topik Kemacetan Lalu Lintas Indonesia Melalui Tweet

Romindo, Romindo (Unknown)
Barus, Okky Putra (Unknown)
Pangaribuan, Jefri Junifer (Unknown)



Article Info

Publish Date
30 Apr 2024

Abstract

The causes of traffic congestion in Indonesia include traffic accidents, poor road infrastructure, and the increasing number of motor vehicles. In 2023, the number of vehicles reached 152.6 million, exceeding half of Indonesia's population of 276 million, according to the Indonesian Traffic Police Corps data. Twitter has a user base of approximately 4.23% of the total global population, which amounts to 436 million user and Indonesia is one of the countries with the largest number of Twitter users. Twitter data will be used to determine the sentiment level of traffic congestion in Indonesia using the Naïve Bayes Classifier method to evaluate overall accuracy performance, precision, recall, and f1-score. The research classified two groups, negative and positive. Classification is carried out through several stages, including data pre-processing, data training, data testing, and evaluation. After evaluating the Naive Bayes algorithm, the highest results achieved an overall accuracy of 77%, precision of 86%, recall of 82%, and f1-score of 84%.

Copyrights © 2024






Journal Info

Abbrev

mib

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Description

Decission Support System, Expert System, Informatics tecnique, Information System, Cryptography, Networking, Security, Computer Science, Image Processing, Artificial Inteligence, Steganography etc (related to informatics and computer ...