Sentimen Analisis Pembatalan Indonesia Menjadi Tuan Rumah Piala Dunia U-20 Menggunakan Metode Naïve Bayes
Abstract
Football is the most popular sport in the world, including Indonesia. Several football tournaments have been postponed due to Covid-19, including the U-20 World Cup which will be held this year in Indonesia. However, the tournament was rejected by several parties who did not want one of the participating countries to take part in the tournament. As a result, the FIFA federation canceled Indonesia as the host for the 2023 U-20 World Cup. The polemic that has occurred in the last few weeks has generated many opinions and opinions from social media users, one of which is Twitter. This study focuses on classifying opinions from tweets on Twitter regarding the cancellation of Indonesia from hosting the U-20 World Cup. This sentiment classification uses the Lexicon Based method to determine positive, negative and neutral sentiments, classification uses the Multinomial Naïve Bayes method for calculating accuracy with the Confusion Matrix. Based on the system built, an accuracy of 85% is obtained with a precision of 85%, a recall of 85%, and an f1-score value of 83%.
Downloads
References
M. I. Fikri, T. S. Sabrila, and Y. Azhar, “Perbandingan Metode Naïve Bayes dan Support Vector Machine pada Analisis Sentimen Twitter,” Smatika J., vol. 10, no. 02, pp. 71–76, 2020, doi: 10.32664/smatika.v10i02.455.
Y. Yudhanto and A. Putra, “Perancangan Dan Pembuatan Sistem Kompetisi Sepak Bola Berbasis Web,” Indones. J. Appl. Informatics, vol. 1, no. 2, p. 23, 2017, doi: 10.20961/ijai.v1i2.14330.
I. Indriati, M. Marji, and S. Pakpahan, “Analisis Sentimen Tentang Opini Performa Klub Sepak Bola Pada Dokumen Twitter Menggunakan Support Vector Machine Dengan Perbaikan Kata Tidak Baku,” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 3, no. 7, pp. 7259–7267, 2019.
M. H. Sidik, S. Widiyanesti, and ..., “Analisis Sentimen dan Topic Modelling Terhadap Tim Nasional Indonesia di Kejuaraan AFF Suzuki Cup 2020 Berdasarkan Opini Pengguna Twitter,” eProceedings …, vol. 9, no. 5, pp. 2783–2796, 2022, [Online]. Available: https://openlibrarypublications.telkomuniversity.ac.id/index.php/management/article/view/18369%0Ahttps://openlibrarypublications.telkomuniversity.ac.id/index.php/management/article/download/18369/17980
R. Lasepa, S. Riyadi, S. Ramadhan, and D. D. Saputra, “Analisis Sentimen Terhadap Perspektif Warganet Atas Tragedi Kanjuruhan Malang di Twitter Menggunakan Naïve Bayes Classifier,” vol. 8, no. 1, pp. 1–8, 2021.
N. Hendrastuty et al., “Analisis Sentimen Masyarakat Terhadap Program Kartu Prakerja Pada Twitter Dengan Metode Support Vector Machine,” J. Inform. J. Pengemb. IT, vol. 6, no. 3, pp. 150–155, 2021, [Online]. Available: http://situs.com
S. S. Salim and J. Mayary, “Analisis Sentimen Pengguna Twitter Terhadap Dompet Elektronik Dengan Metode Lexicon Based Dan K – Nearest Neighbor,” J. Ilm. Inform. Komput., vol. 25, no. 1, pp. 1–17, 2020, doi: 10.35760/ik.2020.v25i1.2411.
D. Rusdiaman and D. Rosiyadi, “Analisa Sentimen Terhadap Tokoh Publik Menggunakan Metode Naïve Bayes Classifier Dan Support Vector Machine,” J. Comput. Eng. Syst. Sci., vol. 4, no. 2, pp. 230–235, 2019.
I. S. Thalib, S. K. Gusti, F. Yanto, and M. Affandes, “Klasifikasi Sentimen Tragedi Kanjuruhan Pada Twitter Menggunakan Algoritma Naïve Bayes,” vol. 4, pp. 467–473, 2023, doi: 10.30865/json.v4i3.5852.
C. Of, N. Bayes, S. Vector, M. For, and A. Twitter, “Perbandingan Metode Naïve Bayes Classifier Dan Support Vector Machine Untuk Analisis Sentimen Pengguna Twitter Mengenai Piala Dunia Fifa 2022,” vol. 13, no. 01, 2023.
J. A. Septian, T. M. Fachrudin, and A. Nugroho, “Analisis Sentimen Pengguna Twitter Terhadap Polemik Persepakbolaan Indonesia Menggunakan Pembobotan TF-IDF dan K-Nearest Neighbor,” J. Intell. Syst. Comput., vol. 1, no. 1, pp. 43–49, 2019, doi: 10.52985/insyst.v1i1.36.
M. M. S. Reino Prajamukti, Jayanta, “Klasifikasi Dan Analisis Sentimen Pada Data Twitter Menggunakan Algoritma Naïve Bayes ( Studi kasus :Timnas Indonesia Senior,U-23, dan u-19),” Seinasi-Kesi, pp. 1–8, 2021, [Online]. Available: https://conference.upnvj.ac.id/index.php/seinasikesi/article/view/1909
M. I. Yusuf, “Analisis Sentimen Komentar Netizen Instagram Terhadap Racism Di Sepak Bola Indonesia Dengan Metode Naive Bayes,” vol. 2, pp. 1–8, 2022.
N. S. Wardani, A. Prahutama, and P. Kartikasari, “Analisis Sentimen Pemindahan Ibu Kota Negara Dengan Klasifikasi Naïve Bayes Untuk Model Bernoulli Dan Multinomial,” J. Gaussian, vol. 9, no. 3, pp. 237–246, 2020, doi: 10.14710/j.gauss.v9i3.27963.
D. Ramadhan and E. B. Setiawan, “Analisis Sentimen Program Acara di SCTV pada Twitter Menggunakan Metode Naive Bayes dan Support Vector Machine,” … .Telkomuniversity.Ac.Id, vol. 6, no. 2, pp. 9736–9743, 2019, [Online]. Available: https://openlibrarypublications.telkomuniversity.ac.id/index.php/engineering/article/view/10708
M. Undap, V. P. Rantung, and P. T. D. Rompas, “Analisis Sentimen Situs Pembajak Artikel Penelitian Menggunakan Metode Lexicon-Based,” Jointer - J. Informatics Eng., vol. 2, no. 02, pp. 39–46, 2021, doi: 10.53682/jointer.v2i02.44.
A. Rosadi et al., “Analisis Sentimen Berdasarkan Opini Pengguna pada Media Twitter Terhadap BPJS Menggunakan Metode Lexicon Based dan Naïve Bayes Classifier,” J. Ilm. Komputasi, vol. 20, no. 1, pp. 39–52, 2021, doi: 10.32409/jikstik.20.1.401.
D. Musfiroh, U. Khaira, P. E. P. Utomo, and T. Suratno, “Analisis Sentimen terhadap Perkuliahan Daring di Indonesia dari Twitter Dataset Menggunakan InSet Lexicon,” MALCOM Indones. J. Mach. Learn. Comput. Sci., vol. 1, no. 1, pp. 24–33, 2021, doi: 10.57152/malcom.v1i1.20.
P. A. Sumitro, Rasiban, D. I. Mulyana, and W. Saputro, “Analisis Sentimen Terhadap Vaksin Covid-19 di Indonesia pada Twitter Menggunakan Metode Lexicon Based,” J-ICOM - J. Inform. dan Teknol. Komput., vol. 2, no. 2, pp. 50–56, 2021, doi: 10.33059/j-icom.v2i2.4009.
D. Winarso, Yanda Noor Yudha, and Syahril, “Analisis Sentimen Masyarakat Pada Twiter Terhadap Isu Covid-19 Menggunakan Metode Lexicon Based,” J. Fasilkom, vol. 11, no. 2, pp. 97–103, 2021, doi: 10.37859/jf.v11i2.2772.
A. Syakur, “Implementasi Metode Lexicon Base Untuk Analisis Sentimen Kebijakan Pemerintah Dalam Pencegahan Penyebaran Virus Corona Covid-19 Pada Twitter,” J. Ilm. Inform. Komput., vol. 26, no. 3, pp. 247–260, 2021, doi: 10.35760/ik.2021.v26i3.4720.
B. M. Pintoko and K. M. L., “Analisis Sentimen Jasa Transportasi Online pada Twitter Menggunakan Metode Naive Bayes Classifier,” e-Proceeding Eng., vol. 5, no. 3, pp. 8121–8130, 2018.
B. Gunawan, H. S. Pratiwi, and E. E. Pratama, “Sistem Analisis Sentimen pada Ulasan Produk Menggunakan Metode Naive Bayes,” J. Edukasi dan Penelit. Inform., vol. 4, no. 2, p. 113, 2018, doi: 10.26418/jp.v4i2.27526.
K. V. S. Toy, Y. A. Sari, and I. Cholissodin, “Analisis Sentimen Twitter menggunakan Metode Naive Bayes dengan Relevance Frequency Feature Selection (Studi Kasus: Opini Masyarakat mengenai Kebijakan New Normal),” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 5, no. 11, pp. 5068–5074, 2021, [Online]. Available: http://j-ptiik.ub.ac.id
A. A. Farisi, Y. Sibaroni, and S. Al Faraby, “Sentiment analysis on hotel reviews using Multinomial Naïve Bayes classifier,” J. Phys. Conf. Ser., vol. 1192, no. 1, 2019, doi: 10.1088/1742-6596/1192/1/012024.
M. M. Mala Olhang, S. Achmadi, and F. . A. Wibisono, “Analisis Sentimen Pengguna Twitter Terhadap Covid-19 Di Indonesia Menggunakan Metode Naive Bayes Classifier (Nbc),” JATI (Jurnal Mhs. Tek. Inform., vol. 4, no. 2, pp. 214–221, 2020, doi: 10.36040/jati.v4i2.2695.
A. Z. Malik, E. Utami, and S. Raharjo, “Analisis Sentiment Twitter Terhadap Capres Indonesia 2019 dengan Metode K-NN,” J. Inf. Politek. Indones. Surakarta, vol. 5, no. 2, pp. 1–7, 2019.
Yuyun, Nurul Hidayah, and Supriadi Sahibu, “Algoritma Multinomial Naïve Bayes Untuk Klasifikasi Sentimen Pemerintah Terhadap Penanganan Covid-19 Menggunakan Data Twitter,” J. RESTI (Rekayasa Sist. dan Teknol. Informasi), vol. 5, no. 4, pp. 820–826, 2021, doi: 10.29207/resti.v5i4.3146.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Sentimen Analisis Pembatalan Indonesia Menjadi Tuan Rumah Piala Dunia U-20 Menggunakan Metode Naïve Bayes
Pages: 1387-1394
Copyright (c) 2023 Setiya Nugroho, Nugroho, Rozaq Sulastiyono, Agus Setiawan, Agus Setiawan

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).






















