SENTIMENT ANALYSIS ON THE CHANGE OF COACH OF THE INDONESIAN NATIONAL TEAM USING SUPPORT VECTOR MACHINE ALGORITHM

Nanda Syamia; Mhd.  Furqan

doi:10.54209/jatilima.v7i02.1510

Nanda Syamia UINSU
Mhd. Furqan Universitas Islam Negeri Sumatera Utara, Indonesia

DOI: https://doi.org/10.54209/jatilima.v7i02.1510

Keywords: Indonesian National Team, Sentiment Analysis, Support Vector Machine, Social Media, TF-IDF.

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Abstract

The change in the coach of the Indonesian national team has ignited a range of public responses on social media, particularly on the X platform (formerly Twitter). This research intends to examine public opinion regarding the firing of coach Shin Tae-yong and the hiring of Patrick Kluivert through the Support Vector Machine (SVM) algorithm. A dataset of 1,000 public comments was gathered via crawling methods from the @timnasindonesia account, subsequently classified as either positive or negative sentiment using a lexicon-based technique. The stages of the research involved text preprocessing (cleaning, tokenization, stemming, and stopword elimination), word weighting through TF-IDF, and sentiment classification with the SVM algorithm. Initial findings indicated a classification accuracy of 77%, which rose to 83% following upsampling to rectify class imbalance. The evaluation of the model utilized a confusion matrix, resulting in high precision, recall, and F1-score metrics. This research shows that SVM is successful in categorizing public sentiment on particular social matters and can serve as a data-informed decision-making resource. These findings further enhance understanding of public views on strategic policies within national sports, especially football.

References

Adhiatma, F. D., & Qoiriah, A. (2022). Penerapan Metode TF-IDF dan Deep Neural Network untuk Analisa Sentimen pada Data Ulasan Hotel. Journal of Informatics and Computer Science (JINACS), xx, 183–193. https://doi.org/10.26740/jinacs.v4n02.p183-193
Andika, H., Pangestu, S., & Kurniawan, T. (2025). Sepak Bola Tanah Air Mulai Dipandang, Pergantian Pelatih Timnas Indonesia Jadi Sorotan Dunia. https://skor.id/post/sepak-bola-tanah-air-mulai-dipandang-pergantian-pelatih-timnas-indonesia-jadi-sorotan-dunia
Bei, F., & Sudin, S. (2021). Analisis Sentimen Aplikasi Tiket Online Di Play Store Menggunakan Metode Support Vector Machine (Svm). Sismatik, 01(01), 91–97.
Faidh, M. A., Maulana, M. E., Putri, N. E., Putri, I., Munir, T. A., Laksana, A., Studi, P., Komunikasi, I., Ilmu, F., Bina, U., Kampus, A., Raya, J., No, K. M., & Jaya, K. C. (2024). Peran Media Sosial X Dalam Perkembangan Komunikasi Di Era Digital. 1, 43–51. https://doi.org/10.62383/konsensus.v1i6.433
Fardi Rizal. (2025). Kontroversi saat Pergantian Pelatih Timnas Indonesia, Shin Tae-yong Bukan yang Pertama. https://www.liputan6.com/hot/read/5870354/kontroversi-saat-pergantian-pelatih-timnas-indonesia-shin-tae-yong-bukan-yang-pertama
Furqan, M., Amanda Putri, R., Agus Martua Daulay, I., William Iskandar Ps, J. V, Estate, M., Deli Serdang, K., & Kunci, K. (2024). Jika | 477 Implementasi Text Mining Dalam Identifikasi Cyber Hate Speech Menggunakan Support Vector Machine. Jurnal Informatika) Universitas Muhammadiyah Tangerang P, 8(4), 2722–2713.
Furqan, M., Hasibuan, M. S., & Sapitri, B. (2023). Application of the support vector machine algorithm in the classification of livable houses. Jurnal Mantik, 7(3), 1643–1652.
Furqan, M., Kurniawan, R., & HP, K. I. (2020). Evaluasi Performa Support Vector Machine Classifier Terhadap Penyakit Mental. Jurnal Sistem Informasi Bisnis, 10(2), 203–210. https://doi.org/10.21456/vol10iss2pp203-210
Furqan, M., & Nasir, A. F. A. (2024). Big Data Approach To Sentiment Analysis in Machine Learning-Based Microblogs: Perspectives of Religious Moderation Public Policy in Indonesia. Journal of Applied Engineering and Technological Science, 5(2), 955–965. https://doi.org/10.37385/jaets.v5i2.4498
Handayani, A., & Zufria, I. (2023). Analisis Sentimen Terhadap Bakal Capres RI 2024 di Twitter Menggunakan Algoritma SVM. Journal of Information System Research (JOSH), 5(1), 53–63. https://doi.org/10.47065/josh.v5i1.4379
Isnain, A. R., Sakti, A. I., Alita, D., & Marga, N. S. (2021). Sentimen Analisis Publik Terhadap Kebijakan Lockdown Pemerintah Jakarta Menggunakan Algoritma Svm. Jurnal Data Mining Dan Sistem Informasi, 2(1), 31. https://doi.org/10.33365/jdmsi.v2i1.1021
Mahendrajaya, R., Buntoro, G. A., & Setyawan, M. B. (2020). Analisis Sentimen Pengguna Gopay Menggunakan Metode Lexicon Based Dan Support Vector Machine. Komputer, 3(2), 52. https://doi.org/10.24269/jkt.v3i2.270
Manalu, B. U. (2020). Modul : Pengantar Python dengan Google Colab. 1–2.
Maritim, J. S. (2022). E-learning merupakan salah cara pembelajaran yang digunakan oleh pengajar untuk melakukan pembelajaran . Pembelajaran e-learning mulai digunakan karena dalam dua tahun terakhir Indonesia mengalami pandemi covid-19 sehingga pembelajaran tidak dilakukan den. 23(September), 97–108.
Nur, M. A., & Saihu, Ma. (2024). PENGOLAHAN SEBUAH DATA. Jurnal Ilmiah Sains Dan Teknologi, 15(1), 37–48.
Syam, A. A., M, G. H., Salim, A., Surianto, D. F., & B, M. F. (2024). Analisis teknik preprocessing pada sentimen masyarakat terkait konflik israel-palestina menggunakan support vector machine. 9(3), 1464–1472.
Thoriq, E. M., Ratnawati, D. E., & Rahayudi, B. (2021). Analisis Sentimen Opini Publik pada Media Sosial Twitter terhadap Vaksin Covid-19 menggunakan Algoritma Support Vector Machine dan Term Frequency-Inverse Document Frequency. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 5(12), 5349–5355.
Wisnu Triyogo. (2025). Di Balik Keputusan Pemecatan Shin Tae-yong dari Kursi Pelatih Timnas Indonesia. https://www.tempo.co/sepakbola/di-balik-keputusan-pemecatan-shin-tae-yong-dari-kursi-pelatih-timnas-indonesia-1190840
Zufria, I., Lubis, A. H., & Febiyaula, S. S. (2024). Analisis Sentimen Kepercayaan Masyarakat Terhadap Kepolisian Republik Indonesia Menggunakan Algoritma Svm. Journal of Science and Social Research, 4307(3), 1266–1272.
Zuniananta, L. E. (2021). Penggunaan Media Sosial sebagai Media Komunikasi Informasi Di Perpustakaan. Jurnal Ilmu Perpustakaan, 10(4), 37–42.