Analisis Sentimen Naturalisasi Tim Nasional Indonesia U-23 di Era Shin Tae-yong Menggunakan Algoritma Naïve Bayes dan K-Nearest Neighbors
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Sep 30, 2024
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In the Shin Tae-yong era, the naturalization of players has become a controversial topic within the Indonesian U-23 national football team. This research aims to analyze public sentiment related to the naturalization of players in the team using two classification algorithms, namely Naive Bayes and K-Nearest Neighbor. Sentiment data is obtained from news sources, social media, and online discussion forums related to matches and team management decisions. First, data processing is carried out, including text cleaning, tokenization, and word weighting. Next, Naive Bayes and KNN models are trained using the processed dataset. The results of the sentiment analysis will provide valuable insight into the public's perception of the naturalization of players in the Indonesian U-23 national team under the control of Shin Tae-yong, as well as a comparison of the effectiveness between the Naive Bayes and KNN algorithms in sentiment classification. It is hoped that this research will provide a more in-depth view of the dynamics within the Indonesian national football team and its contribution to Indonesian football as a whole
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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
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Fauzi, M. A., Mentari, N. D., & Muflikhah, L. (2018). Analisis sentimen kurikulum 2013 pada sosial media Twitter menggunakan metode K-Nearest Neighbor dan feature selection. Query Expansion Ranking Optimasi Sisa Bahan Baku Pada Industri Mebel Menggunakan Algoritma Genetika View Project Human Detection and Tra, 2(8), 2739–2743. https://www.researchgate.net/publication/322959504
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Muttaqin, M. N., & Kharisudin, I. (2021). Analisis sentimen pada ulasan aplikasi Gojek menggunakan metode Support Vector Machine dan K-Nearest Neighbor. UNNES Journal of Mathematics, 10(2), 22–27. http://journal.unnes.ac.id/sju/index.php/ujm
Nugroho, D. G., Chrisnanto, Y. H., & Wahana, A. (2015). Analisis sentimen pada jasa ojek online. Jurnal, 156–161.
Nurhuda, F., Widya Sihwi, S., & Doewes, A. (2016). Analisis sentimen masyarakat terhadap calon presiden Indonesia 2014 berdasarkan opini dari Twitter menggunakan metode Naive Bayes classifier. Jurnal Teknologi & Informasi ITSmart, 2(2), 35. https://doi.org/10.20961/its.v2i2.630
Prabowo, W. A., & Wiguna, C. (2021). Sistem informasi UMKM bengkel berbasis web menggunakan metode SCRUM. Jurnal Media Informatika Budidarma, 5(1), 149. https://doi.org/10.30865/mib.v5i1.2604
Pratama, A. E., Ariesta, A., & Gata, G. (2022). Analisis sentimen masyarakat terhadap Tim Nasional Indonesia pada Piala AFF 2020 menggunakan algoritma K-Nearest Neighbors. Jurnal TICOM: Technology of Information and Communication, 10(3), 187–196. https://jurnal-ticom.jakarta.aptikom.org/index.php/Ticom/article/view/33/47
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Salim, S. S., & Mayary, J. (2020). Analisis sentimen pengguna Twitter terhadap dompet elektronik dengan metode Lexicon Based dan K-Nearest Neighbor. Jurnal Ilmiah Informatika Komputer, 25(1), 1–17. https://doi.org/10.35760/ik.2020.v25i1.2411
Sari, P. K., & Suryono, R. R. (2024). Komparasi algoritma Support Vector Machine dan Random Forest untuk analisis sentimen metaverse. Jurnal Mnemonic, 7(1), 31–39. https://doi.org/10.36040/mnemonic.v7i1.8977
Sari, R. (2020). Analisis sentimen pada review objek wisata Dunia Fantasi menggunakan algoritma K-Nearest Neighbor (K-NN). EVOLUSI: Jurnal Sains dan Manajemen, 8(1), 10–17. https://doi.org/10.31294/evolusi.v8i1.7371
Sembada, A. D., & Prasetyo, D. (2020). Aktualisasi Pancasila dalam sepak bola Indonesia. CIVICUS: Pendidikan-Penelitian-Pengabdian Pendidikan Pancasila dan Kewarganegaraan, 8(2), 1. https://doi.org/10.31764/civicus.v8i2.2410
Setiawan, H., & Zufria, I. (2023). Analisis sentimen pembatalan Indonesia sebagai tuan rumah Piala Dunia FIFA U-20 menggunakan Naïve Bayes. Jurnal Media Informatika Budidarma, 7(3), 1003–1012. https://doi.org/10.30865/mib.v7i3.6144
Sipayung, E. M., Maharani, H., & Zefanya, I. (2016). Perancangan sistem analisis sentimen komentar pelanggan menggunakan metode Naive Bayes classifier. Jurnal Sistem Informasi (JSI), 8(1), 2355–4614. http://ejournal.unsri.ac.id/index.php/jsi/index
Supriyanto, J., Alita, D., & Isnain, A. R. (2023). Penerapan algoritma K-Nearest Neighbor (K-NN) untuk analisis sentimen publik terhadap pembelajaran daring. Jurnal Informatika dan Rekayasa Perangkat Lunak, 4(1), 74–80. https://doi.org/10.33365/jatika.v4i1.2468.