Analisis Sentimen Pemecatan Shin Tae-yong pada Media Sosial X untuk Monitoring Opini Publik Menggunakan Naïve Bayes dan Support Vector Machines

Ni Luh Bumi Arisenja; Dadang Iskandar Mulyana

doi:10.63447/jimik.v6i3.1561

Vol. 6 No. 3 (2025) • Articles

Open Access

Analisis Sentimen Pemecatan Shin Tae-yong pada Media Sosial X untuk Monitoring Opini Publik Menggunakan Naïve Bayes dan Support Vector Machines

Ni Luh Bumi Arisenja

Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika

Dadang Iskandar Mulyana

Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika

DOI: https://doi.org/10.63447/jimik.v6i3.1561

Published: September 10, 2025 Pages: 1694-1705

Original Full-Text Article

Download published version for reading and archiving

Download PDF

Abstract

Social media has become a primary platform for people to voice their opinions on national issues, including in the field of sports. One of the hotly discussed issues is the dismissal of the Indonesian National Team coach, Shin Tae-Yong. This study aims to analyze public sentiment towards the dismissal through social media platform X (formerly known as Twitter) using two machine learning algorithms, namely Naïve Bayes and Support Vector Machines (SVM). Data was obtained through a crawling process using the keyword pecat shin tae-yong, then carried out pre-processing stages such as cleaning, tokenizing, stopword removal, and stemming. The evaluation process was carried out using a confusion matrix to measure accuracy, precision, recall, and F1-score. The classification results show that the Naïve Bayes model produces an accuracy of 92.91%, while the positive precision value is 81.33%, and the negative precision is 100%. Meanwhile, the SVM (Support Vector Machine) model provided more optimal results with an accuracy of 97.97%, a positive precision of 96.72%, a negative precision of 98.53%, and a positive recall of 96.72% and a negative recall of 98.53%. Based on these results, it can be concluded that the SVM algorithm performed better in analyzing public opinion regarding the coach's dismissal issue. This research is expected to contribute as a reference data-based public opinion monitoring system for more transparent public policymaking.

Keywords:

Sentiment Analysis Shin Tae-Yong Naïve Bayes SVM Social Media X

Article Metrics & Downloads Graph

Monthly Download Trends:

Author Biographies

Ni Luh Bumi Arisenja Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika

Program Studi Sistem Informasi, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.

Dadang Iskandar Mulyana Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika

Program Studi Sistem Informasi, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.

How to Cite

Arisenja, N. L. B., & Mulyana, D. I. (2025). Analisis Sentimen Pemecatan Shin Tae-yong pada Media Sosial X untuk Monitoring Opini Publik Menggunakan Naïve Bayes dan Support Vector Machines. Jurnal Indonesia : Manajemen Informatika Dan Komunikasi, 6(3), 1694-1705. https://doi.org/10.63447/jimik.v6i3.1561

License

Creative Commons Attribution 4.0 International License (CC BY 4.0)

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License .

Share: You are free to copy, distribute, and transmit the work in any medium or format.
Adapt: You are free to remix, transform, and build upon the work for any purpose, even commercially.
Attribution: You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

Copyright & Retention: Authors retain copyright without restrictions and grant this journal the right of first publication under an open-access model. The journal retains non-exclusive publishing rights for archiving, indexing, and scholarly dissemination.

References

Total: 15 References

Aldisa, R. T., & Maulana, P. (2022). Analisis Sentimen Opini Masyarakat Terhadap Vaksinasi Booster COVID-19 Dengan Perbandingan Metode Naive Bayes, Decision Tree dan SVM. Building of Informatics, Technology and Science (BITS), 4(1), 106-109.
Alfiyani, W., Fatah, D. A., & Irhamni, F. (2025). PENERAPAN ALGORITMA NAÏVE BAYES UNTUK ANALISIS SENTIMEN PADA MEDIA SOSIAL X TERHADAP PERFORMA TIM NASIONAL SEPAK BOLA INDONESIA DI ERA KEPEMIMPINAN SHIN TAE-YONG. JATI (Jurnal Mahasiswa Teknik Informatika), 9(3), 3969-3977.
Anastasya, T. A., Saka, A. D. P., Deke, M. J. D., & Rizki, A. M. (2025). OPTIMASI ALGORITMA SVM DENGAN PSO UNTUK ANALISIS SENTIMEN PADA MEDIA SOSIAL X TERHADAP KINERJA TIMNAS DI ERA SHIN TAE-YONG. JATI (Jurnal Mahasiswa Teknik Informatika), 9(1), 384-391.
Berliani, S., & Lestari, S. (2024). Analisis Sentimen Masyarakat Terhadap Isu Pecat Sri Mulyani Pada Twitter Menggunakan Metode Naive Bayes Dan Support Vector Machine. Jurnal Sains dan Teknologi, 5(3), 951-960. https://doi.org/10.55338/saintek.v5i3.2746.
Damanik, F. J., & Setyohadi, D. B. (2021, March). Analysis of public sentiment about COVID-19 in Indonesia on Twitter using multinomial naive bayes and support vector machine. In IOP Conference Series: Earth and Environmental Science (Vol. 704, No. 1, p. 012027). IOP Publishing.

Indriyani, F. A., Fauzi, A., & Faisal, S. (2023). Analisis sentimen aplikasi tiktok menggunakan algoritma naïve bayes dan support vector machine. TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika, 10(2), 176-184. https://doi.org/10.37373/tekno.v10i2.419.
Jaya, D. R. P., & Lestari, S. (2024). Analisis Sentimen Naturalisasi Tim Nasional Indonesia U-23 di Era Shin Tae-yong Menggunakan Algoritma Naïve Bayes dan K-Nearest Neighbors. Jurnal Indonesia: Manajemen Informatika dan Komunikasi, 5(3), 3262-3277. https://doi.org/10.35870/jimik.v5i3.1024.
Maulana, B. A., Fahmi, M. J., Imran, A. M., & Hidayati, N. (2024). Analisis Sentimen Terhadap Aplikasi Pluang Menggunakan Algoritma Naive Bayes dan Support Vector Machine (SVM): Sentiment Analysis of Pluang Applications With Naive Bayes and Support Vector Machine (SVM) Algorithm. MALCOM: Indonesian Journal of Machine Learning and Computer Science, 4(2), 375-384. https://doi.org/10.57152/malcom.v4i2.1206.
Noviana, R., & Rasal, I. (2023). Penerapan Algoritma Naive Bayes Dan Svm Untuk Analisis Sentimen Boy Band Bts Pada Media Sosial Twitter. Jurnal Teknik dan Science, 2(2), 51-60.
Sarimole, F. M., & Kudrat, K. (2024). Analisis Sentimen Terhadap Aplikasi Satu Sehat Pada Twitter Menggunakan Algoritma Naive Bayes Dan Support Vector Machine. Jurnal Sains dan Teknologi, 5(3), 783-790. https://doi.org/10.55338/saintek.v5i3.2702.
Sembiring, H. P., Ridho, I. M., & Loveressa, Z. (2025). Pengaruh Shin-Tae Yong Terhadap Kepuasan Suporter Timnas Indonesia. Jurnal Ilmu Komunikasi Dan Sosial Politik, 2(3), 631-635.
Sembrani, B. G. (2025). Pengaruh Terpaan Informasi Pemecatan Shin Tae-yong Dan Persepsi Pada PSSI Terhadap Reputasi PSSI. Interaksi Online, 13(3).
Septian, W., & Sarimole, F. M. (2024). Komparasi Analisis Sentimen Masyarakat Terhadap Isu Penundaan Pemilu 2024 Pada Twitter Dengan Metode Naive Bayes Dan Support Vector Machine. Jurnal Sains dan Teknologi, 5(3), 890-899. https://doi.org/10.55338/saintek.v5i3.2789.
Styawati, S., Isnain, A. R., Hendrastuty, N., & Andraini, L. (2021). Comparison of Support Vector Machine and Naïve Bayes on Twitter Data Sentiment Analysis. Jurnal Informatika: Jurnal Pengembangan IT, 6(1), 56-60.
Zuhrival, G. E. (2024). Analisis Sentimen Performa Tim Nasional Sepak Bola Indonesia Era Kepemimpinan Shin Tae-yong pada X Menggunakan Algoritma Naive Bayes (Doctoral dissertation, Universitas Islam Indonesia).