Sentiment analysis of the 2024 election using the naïve bayes method using data x

Authors

  • Ahmad Halim Faizal Zidan Universitas Teknologi Yogyakarta, Indonesia
  • Irma Handayani Universitas Teknologi Yogyakarta, Indonesia
  • Afwan Anggara Universitas Teknologi Yogyakarta, Indonesia

DOI:

https://doi.org/10.35335/mandiri.v14i2.471

Keywords:

2024 Indonesian General Election, Naive Bayes, Social Media X, Text Mining

Abstract

Text mining is a process for utilizing the vast amounts of data generated in today’s digital era. The rapid growth of social media usage has produced extensive textual data, one of which can be analyzed through sentiment analysis. This study uses the social media platform X to analyze public opinions regarding the 2024 Indonesian General Election. The analysis was conducted using 126 user comments as the dataset and 103 reviews as the testing data, which were then processed using the Naive Bayes method. Text mining with the Naive Bayes algorithm can be applied to examine public opinions and sentiments toward the 2024 election on X. The results of the analysis classify sentiments into positive, negative, and neutral categories.

References

Adi Setiawan, H. R. (2022). Klasifikasi Kepribadian Berdasarkan Postingantwitter Dengan Algoritme Naïve Bayes Studikasus : Cv. Wilis Elektronik. Klasifikasi Kepribadian Berdasarkan Postingan Twitter Dengan Algoritme Naïve Bayes Studi Kasus : Cv. Wilis Elektronik, 4(2), 1–13. Https://Www.Researchgate.Net/Publication/367400472_Klasifikasi_Kepribadian_Seseorang_Berdasarkan_Postingan_Twitter_Dengan_Algoritma_Naive_Bayes_Classification_Studi_Kasus_Cv_Wilis_Elektronik

Albab, M. U., P., Y. K., & Fawaiq, M. N. (2023). Optimization Of The Stemming Technique On Text Preprocessing President 3 Periods Topic. Jurnal Transformatika, 20(2), 1–12. Https://Doi.Org/10.26623/Transformatika.V20i2.5374

Alisya Mutia Mantika, Agung Triayudi, & Rima Tamara Aldisa. (2024). Sentiment Analysis On Twitter Using Naïve Bayes And Logistic Regression For The 2024 Presidential Election. Sana: Journal Of Blockchain, Nfts And Metaverse Technology, 2(1), 44–55. Https://Doi.Org/10.58905/Sana.V2i1.267

Arsi, P., & Waluyo, R. (2021). Sentiment Analysis Of Discourse On Moving The Indonesian Capital City Using The Support Vector Machine (Svm) Algorithm. Jurnal Teknologi Informasi Dan Ilmu Komputer, 8(1), 147. Https://Doi.Org/10.25126/Jtiik.202183944

Asro, Chairuddin, & Robi, P. A. (2023). Hci Dan Media Sosial: Studi Kasus Analisis Sentimen Pilpres 2024 Di Twitter Menggunakan Naive Bayes Classifier. Jurnal Simetris, 14(2), 297–309.

Aulia, Z. (2021). Analisis Perancangan Sistem Informasi Sekolah Menengah Kejuruan 1 Gandapura Dengan Model Diagram Konteks Dan Data Flow Diagram. Jurnal Teknologi Terapan And Sains 4.0, 2, 5–2.

Deolika, A., Kusrini, K., & Luthfi, E. T. (2019). Analisis Pembobotan Kata Pada Klasifikasi Text Mining. Jurnal Teknologi Informasi, 3(2), 179. Https://Doi.Org/10.36294/Jurti.V3i2.1077

Fais Sya’ Bani, M. R., Enri, U., & Padilah, T. N. (2022). Analisis Sentimen Terhadap Bakal Calon Presiden 2024 Dengan Algoritme Naïve Bayes. Jurikom (Jurnal Riset Komputer), 9(2), 265. Https://Doi.Org/10.30865/Jurikom.V9i2.3989

Hari, Y., Yanggah, M. E., & Paramita, A. S. (2025). Assessing Novice Voter Resilience On Disinformation During Indonesia Elections 2024 With Naïve Bayes Classifier. Journal Of Applied Data Sciences, 6(1), 299–310. Https://Doi.Org/10.47738/Jads.V6i1.489

Hariyanti, Y., Kacung, S., & Santoso, B. (2024). Analisis Sentimen Terhadap Putusan Mahkamah Konstitusi Tentang Batasan Umur Capres Dan Cawapres Menggunakan Metode Naïve Bayes. Multidisciplinary Indonesian Center Journal (Micjo), 1(1), 517–525. Https://Doi.Org/10.62567/Micjo.V1i1.61

Hermawan, L., & Bellaniar Ismiati, M. (2020). Pembelajaran Text Preprocessing Berbasis Simulator Untuk Mata Kuliah Information Retrieval. Jurnal Transformatika, 17(2), 188–199. Https://Doi.Org/10.26623/Transformatika.V17i2.1705

Hidayat, A. (2020). Manfaat Pelaksanaan Pemilu Untuk Kesejahteraan Masyarakat. Politicon : Jurnal Ilmu Politik, 2(1), 72–85. Https://Doi.Org/10.15575/Politicon.V2i1.7513

Ismawan, I., & Saputra, W. (2024). Analisis Sentimen Publik Terhadap Pelaksanaan Persiapan Pemilu Tahun 2024 Menggunakan Metode Maximum Entropy ( Maxent ). Journal Of Artificial Intelegence & Data Science, 4(1), 22–28.

Mariani, M., Angreni, D. S., Nur, S. K., Rinianty, R., & Jayanto, D. L. (2025). Sentiment Analysis For The 2024 Dki Jakarta Gubernatorial Election Using A Support Vector Machine Approach. Journal Of Applied Informatics And Computing, 9(2), 564–570. Https://Doi.Org/10.30871/Jaic.V9i2.9260

Muliadi, M., Andriani, M., & Irawan, H. (2020). Konteks Diagram. Jisi: Jurnal Integrasi Sistem Industri, 7(2), 111.

Muliana, A. S., Lestarini, D., & Raflesia, S. P. (2024). Analysis Of Public Sentiment On Election Results Using Naïve Bayes In Social Media X. Sistemasi, 13(6), 2467. Https://Doi.Org/10.32520/Stmsi.V13i6.4592

Pramono, B. A., Firman Daru, A., & Ulum, M. B. (2024). Twitter Sentiment Analysis Using Natural Language Processing (Nlp) Method And Long Short Term Memory (Lstm) Algorithm In The 2024 Indonesian Presidential Election. International Journal Of Information Technology And Business, 6(2), 24–30. Http://Ejournal.Uksw.Edu/Ijiteb

Ramadhan, M. A., & Wahyudin, M. I. (2022). Analisis Sentimen Mengenai Keberhasilan Indonesia Di Ajang Thomas Cup 2020 (Studi Kasus Media Sosial Twitter) Menggunakan Metode Naïve Bayes Dan Decision Tree. Jurnal Jtik (Jurnal Teknologi Informasi Dan Komunikasi), 6(4), 505–511. Https://Doi.Org/10.35870/Jtik.V6i4.560

Sholihah, N., Abdulloh, F. F., & Rahardi, M. (2024). Sentiment Analysis On Kpu Performance Post-2024 Election Via Youtube Comments Using Bert. Sinkron, 8(4), 2222–2232. Https://Doi.Org/10.33395/Sinkron.V8i4.14040

Sulaiman, C., Salamah, U. G., Oktaviati, R., & Faizah, S. (2024). Sentiment Analysis And Classification Of Public Opinion On Prabowo Subianto Using Naïve Bayes On Twitter. Journal Of Global Engineering Research And Science, 3(2), 56–62. Https://Doi.Org/10.56904/J-Gers.V3i2.98

Thomas, S., Yuliana, & P, N. (2021). Study Analysis Of Sentiment Analysis Methods On Youtube. Journal Of Information Technology, 1(1), 1–7. Https://Journal.Shantibhuana.Ac.Id/Index.Php/Jifotech/Article/View

Wahyu Nugroho, A., & Susanto, T. (2025). Sentiment Analysis Of Social Media Users On The 2024 Presidential Election Using The Naive Bayes Classifier Method Informasi Artikel Abstrak. Journal Of Artificial Intelligence And Software Engineering, 5(2), 410–420. Https://Doi.Org/10.30811/Jaise.V5i2.6679

Wahyudi, A., Santoso, G. B., & Sholihah, B. (2024). Analysis Of The Sentiment Of Indonesian Presidential Candidates For 2024 On The Youtube Social Media Platform Using The Support Vector Machine Method. Intelmatics, 4(1), 22–30. Https://Doi.Org/10.25105/Itm.V4i1.17636

Yafi, M. (2024). Journal La Multiapp. Teknik Industri, 05(06), 910–922. Https://Doi.Org/10.37899/Journallamultiapp.V5i5.394

Yusuf Ramadhan Nasution, Suhardi Suhardi, & Ilham Hafiz Satrio. (2024). Penerapan Algoritma Klasifikasi Naïve Bayes Untuk Analisis Sentimen Tentang Pemilu 2024. Elkom: Jurnal Elektronika Dan Komputer, 17(2), 495–502. Https://Doi.Org/10.51903/Elkom.V17i2.2053

Downloads

Published

2025-10-29

How to Cite

Zidan, A. H. F., Handayani, I., & Anggara, A. (2025). Sentiment analysis of the 2024 election using the naïve bayes method using data x. Jurnal Mandiri IT, 14(2), 225–234. https://doi.org/10.35335/mandiri.v14i2.471