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All Journal Technomedia Journal
Mauliza, Risha Nur
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Computer Science & IT Languange, Linguistic, Communication & Media

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Penerapan Text Mining Dalam Menganalisis Pendapat Masyarakat Terhadap Pemilu 2024 Pada Media Sosial X Menggunakan Metode Naive Bayes: Application of Text Mining in Analyzing Public Opinions on the 2024 Election on Social Media X Using the Naive Bayes Method Mauliza, Risha Nur; Sipayung, Yoannes Romando
Technomedia Journal Vol 9 No 1 Juni (2024): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v9i1.2212

Abstract

Tetx mining is a process to utilize the ocean of data in the Industrial Age 4.0. The rapid growth in the use of social media has generated a lot of data in the form of text analysis, one of which is sentiment analysis. This research uses social media X in analyzing the sentiment of opinions about the 2024 election. This analysis was taken from X social media user comments as much as 300 review data divided into 2 categories, namely 100 training data and 200 test data, then tested using the naïve bayes method. The text mining method with the naïve bayes algorithm can be applied to analyze public opinion and sentiment towards the 2024 election on the X social media platform. The results of data testing with the naïve bayes method obtained results with the acquisition of 103 positive sentiments, 47 negative sentiments and 50 neutral sentiments.
Co-Authors Yoannes Romando Sipayung