The Indonesian Journal of Computer Science
Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)

OPTIMASI TEKNIK VOTING PADA SENTIMEN ANALISIS PEMILIHAN PRESIDEN 2024 MENGGUNAKAN MACHINE LEARNING

Kharisma Rahayu (Unknown)
M. Khairul Anam (Unknown)
Lusiana Efrizoni (Unknown)
Nurjayadi (Unknown)
Triyani Arita Fitri (Unknown)



Article Info

Publish Date
25 Jul 2024

Abstract

The presidential election is an important event in the democratic system of the Unitary State of the Republic of Indonesia or NKRI held every five years. There are many pros and cons of the presidential election, especially on social media Twitter or X. X is one of the media platforms where people leave positive, neutral, and even negative comments. Therefore, this research aims to build a sentiment analysis model to classify the sentiment of the 2024 presidential election. This research uses the Support Vector machine, Naïve Bayes and Decision Tree algorithms in performing classification with the addition of the Syntethic Minority Over-Sampling and Ensemble Voting methods. The test results show that public sentiment towards the presidential election dominates negative sentiment of 5008 positive 3582 and neutral 1411 sentiments. Then the results of data processing SVM, NB and DT algorithms plus SMOTE and ensemble voting optimization, provide 92.8% accuracy, 93% precision, 93% recall and 93% F1-Score. This research can make a significant contribution by classifying public sentiment towards the 2024 presidential election data.

Copyrights © 2024






Journal Info

Abbrev

ijcs

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering Engineering

Description

The Indonesian Journal of Computer Science (IJCS) is a bimonthly peer-reviewed journal published by AI Society and STMIK Indonesia. IJCS editions will be published at the end of February, April, June, August, October and December. The scope of IJCS includes general computer science, information ...