International Journal Software Engineering and Computer Science (IJSECS)
Vol. 4 No. 1 (2024): APRIL 2024

Application of the Naive Bayes Algorithm in Twitter Sentiment Analysis of 2024 Vice Presidential Candidate Gibran Rakabuming Raka using Rapidminer

Amini, Tasya Aisyah (Unknown)
Setiawan, Kiki (Unknown)



Article Info

Publish Date
20 Apr 2024

Abstract

In the current era of digital democracy, social media sentiment analysis has become a relevant method for understanding public views of political figures. As one of the leading social media platforms, Twitter provides a public space for sharing opinions and expressions regarding political issues. This research aims to classify and measure the accuracy of people's responses to the positive and negative sides. Sentiment analysis was carried out using the Naïve Bayes method using a dataset of 3223 tweets. The final results of this research show that implementing the Naïve Bayes Method in sentiment analysis regarding political dynasty polemics, especially regarding the 2024 Cawapres Gibran Rakabuming Raka, provides an accuracy value of 82.19%. Of the 1696 negative and 112 positive sentiments predicted, there were 462 harmful and 953 positive predicted data. These results indicate that most public responses tend to be detrimental to the Constitutional Court's (MK) decision, which grants political legitimacy to Gibran Rakabuming Raka as the 2024 vice-presidential candidate.

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Journal Info

Abbrev

ijsecs

Publisher

Subject

Computer Science & IT

Description

IJSECS is committed to bridge the theory and practice of information technology and computer science. From innovative ideas to specific algorithms and full system implementations, IJSECS publishes original, peer-reviewed, and high quality articles in the areas of information technology and computer ...