SENTIMENT ANALYSIS OF POTENTIAL 2024 PRESIDENTIAL CANDIDATES ON TWITTER SOCIAL MEDIA USING METHODS NAIVE BAYES MULTINOMIAL
DOI:
https://doi.org/10.61677/jth.v2i3.247Keywords:
Twitter, sentiment analysis, potential presidential candidates 2024Abstract
This research aims to conduct sentiment analysis regarding potential presidential candidates in 2024, so that we can identify candidates who have positive, neutral and negative images in the view of the public on Twitter social media. This sentiment analysis helps candidates understand People's aspirations and adapt their communications accordingly. This research uses the naïve Bayes multinomial method and utilizes crawling technology on Twitter social media, data is collected and analyzed efficiently. The results of this research obtained 6000 comment data with each candidate having 2000 comments. Ganjar Pranowo had the highest positive sentiment (39%), followed by Anies Baswedan (35.8%) and Prabowo Subianto (25.9%). Ganjar also leads in neutral sentiment (38.8%). The highest number of negative sentiments was held by Prabowo Subianto (39.3%), Anies Baswedan (30.5%), Ganjar Pranowo (21.3%). So from these results, Ganjar Pranowo has the best electability based on public comments on Twitter social media.
References
Adhi, M. S., Nafan, M. Z., & Usada, E. (2019). Pengaruh Semantic Expansion pada Naïve Bayes Classifier untuk Analisis Sentimen Tokoh Masyarakat. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 3(2), 141–147. https://doi.org/10.29207/resti.v3i2.901
Andika, L. A., Azizah, P. A. N., & Respatiwulan, R. (2019). Analisis Sentimen Masyarakat terhadap Hasil Quick Count Pemilihan Presiden Indonesia 2019 pada Media Sosial Twitter Menggunakan Metode Naive Bayes Classifier. In Indonesian Journal of Applied Statistics (Vol. 2, Issue 1, p. 34). https://doi.org/10.13057/ijas.v2i1.29998
Aryadillah, A., & Fitriansyah, F. (2022). Strategi Kampanye Politik Anies Baswedan dalam Membangun Citra Politik Pada Pemilihan Presiden Tahun 2024. Jurnal Public Relations (J-PR), 3(1), 87–92. https://doi.org/10.31294/jpr.v3i1.1150
Buntoro, G. A. (2017). Analisis Sentimen Calon Gubernur DKI Jakarta 2017 Di Twitter. Integer Journal, 2(1), 32–41.
Fairuzabadi, M., Sinambela, M., Taju, S. W., Syahrani, A., Arni, S., Yuliansyah, H., Saputra, A. I. H., Stephane, I., Pakpahan, A., Lubis, M., & Liem, A. T. (2024). Data Science: Sebuah Pengantar untuk Pemula. Yayasan Kita Menulis.
Juanita, S. (2020). Analisis Sentimen Persepsi Masyarakat Terhadap Pemilu 2019 Pada Media Sosial Twitter Menggunakan Naive Bayes. Jurnal Media Informatika Budidarma, 4, 552–558.
Nurjanah, W. E., Perdana, R. S., & Fauzi, M. A. (2017). Analisis Sentimen Terhadap Tayangan Televisi Berdasarkan Opini Masyarakat pada Media Sosial Twitter menggunakan Metode K-Nearest Neighbor dan Pembobotan Jumlah Retweet. In Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer e-ISSN (Vol. 2548, p. 964X).
Pradana, A. W., & Hayaty, M. (2019). The Effect of Stemming and Removal of Stopwords on the Accuracy of Sentiment Analysis on Indonesian-language Texts. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 375–380. https://doi.org/10.22219/kinetik.v4i4.912
Putra, A., Haeirudin, D., Khairunnisa, H., & Latifah, R. (2021). Analisis Sentimen Masyarakat Terhadap Kebijakan PPKM Pada Media Sosial Twitter Menggunakan Algoritma SVM. In Seminar Nasional Sains dan Teknologi 2021 (Issue November, pp. 1–6).
Putranti, N. D., & Winarko, E. (2014). Analisis Sentimen Twitter untuk Teks Berbahasa Indonesia dengan Maximum Entropy dan Support Vector Machine. In IJCCS (Indonesian Journal of Computing and Cybernetics Systems) (Vol. 8, Issue 1, p. 91). https://doi.org/10.22146/ijccs.3499
Reynaldhi, M. A. R., & Sibaroni, Y. (2021). Analisis Sentimen Review Film pada Twitter menggunakan Metode Klasifikasi Hybrid Naïve Bayes dan Decision Tree. E-Proceeding of Engineering, 8(5), 10127–10137.
We Are Social & Hootsuite. (2023). Digital 2023: Indonesia. We Are Social. https://wearesocial.com/id/blog/2023/01/digital-2023/
Yasya, W., Muljono, P., Seminar, K. B., & Hardinsyah, H. (2019). Pengaruh Penggunaan Media Sosial Facebook Dan Dukungan Sosial Online Terhadap Perilaku Pemberian Air Susu Ibu. Jurnal Studi Komunikasi Dan Media, 23(1), 71. https://doi.org/10.31445/jskm.2019.1942
Yoga Pratama, A., Umaidah, Y., Voutama, A., Informatika, T., Ilmu Komputer, F., Singaperbangsa Karawang Ds Paseurjaya, U., Telukjambe Timur, K., Karawang, K., & Barat, J. (2021). Analisis Sentimen Media Sosial Twitter Dengan Algoritma K-Nearest Neighbor Dan Seleksi Fitur Chi-Square (Kasus Omnibus Law Cipta Kerja). Jurnal Sains Komputer & Informatika (J-SAKTI, 5(2), 897–910.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 JTH: Journal of Technology and Health
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
