Classification of Public Sentiment Toward 2024 Presidential Candidates on Social Media Platform X Using Naïve Bayes Algorithm

Ramdhan Hakiki; Agung Pambudi; Asriyanik

doi:10.59934/jaiea.v3i2.422

Authors

Ramdhan Hakiki Universitas Muhammadiyah Sukabumi
Agung Pambudi Universitas Muhammadiyah Sukabumi
Asriyanik Universitas Muhammadiyah Sukabumi

DOI:

https://doi.org/10.59934/jaiea.v3i2.422

Keywords:

Sentiment Classification, Naive Bayes, Presidential Candidates

Abstract

This research examines the use of Naïve Bayes algorithm to classify public sentiment on social media X towards Indonesia's 2024 presidential candidates. Against the backdrop of the importance of presidential elections in a democracy, this research focuses on analyzing public sentiment from June to August 2023. The Naïve Bayes method was chosen to process review data about the three main candidates. The classification results provide insight into the positive and negative sentiments of the public, providing benefits for political parties and researchers in understanding public opinion. This research also enhances the understanding of sentiment classification in a political context and provides readers with a useful reference on the Naïve Bayes approach to sentiment classification. In terms of accuracy, the developed naïve bayes model shows a success rate with an accuracy of 74% for Anies Baswedan, 74% for Ganjar, and 88% for Prabowo.

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