Sentiment Analysis on the Centralized Isolation Policy for Covid-19 Response in Bali Province
Submitted : 2022-10-10, Published : 2022-12-31.
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F. K. K. R. Indonesia, “No Title,” 2022. https://www.kemkes.go.id/folder/view/full-content/structure-faq.html .
W. H. Organization, “Coronavirus disease (COVID-19),” 2022. https://www.who.int/health-topics/coronavirus#tab=tab_1.
A. Syauqi, “Jalan panjang covid19 (sebuah refleksi dikala wabah merajalela berdampak pada perekonomian),” JKUBS J. Chem. Inf. Model., vol. 1, no. 1, pp. 1–19, 2020.
R. Feldman and J. Sanger, The Text Mining Handbook. 2006.
Y. A. Mejova, Sentiment analysis within and across social media streams. 2012.
R. Feldman, “Techniques and Applications For Sentiment Analysis,” Commun. ACM, vol. 56, no. 4, pp. 82–89, 2013, doi: 10.1145/2436256.2436274.
Y. Garg and N. Chatterjee, “Sentiment analysis of twitter feeds,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 8883, pp. 33–52, 2014, doi: 10.1007/978-3-319-13820-6.
A. Balahur et al., “Sentiment analysis in the news,” Proc. 7th Int. Conf. Lang. Resour. Eval. Lr. 2010, pp. 2216–2220, 2010.
S. Kiritchenko, X. Zhu, and S. M. Mohammad, “Sentiment analysis of short informal texts,” J. Artif. Intell. Res., vol. 50, pp. 723–762, 2014, doi: 10.1613/jair.4272.
A. Ortigosa, J. M. Martín, and R. M. Carro, “Sentiment analysis in Facebook and its application to e-learning,” Comput. Human Behav., vol. 31, pp. 527–541, Feb. 2014, doi: 10.1016/j.chb.2013.05.024.
W. Medhat, A. Hassan, and H. Korashy, “Sentiment analysis algorithms and applications: A survey,” Ain Shams Eng. J., vol. 5, no. 4, pp. 1093–1113, 2014, doi: 10.1016/j.asej.2014.04.011.
D. Berrar, “Bayes’ theorem and naive bayes classifier,” Encycl. Bioinforma. Comput. Biol. ABC Bioinforma., vol. 1–3, no. September, pp. 403–412, 2018, doi: 10.1016/B978-0-12-809633-8.20473-1.
A. Herdhianto, Sentiment Analysis Menggunakan Naïve Bayes Classifier (NBC) Pada Tweet Tentang Zakat. 2020.
S. D. Harijiatno, “ANALISIS SENTIMEN PADA TWITTER MENGGUNAKAN MULTINOMINAL NAIVE BAYES,” 2019.
I. Susianti, S. S. Ningsih, M. Al Haris, and T. W. Utami, “Analisis Sentimen Pada Twitter Terkait New Normal Dengan Metode Naïve Bayes Classifier,” Pros. Semin. Edusainstech FMIPA UNIMUS, pp. 354–363, 2020, [Online]. Available: https://prosiding.unimus.ac.id/index.php/edusaintek/article/view/576/578.
V. Jayaswal, “Text Vectorization: Term Frequency — Inverse Document Frequency (TFIDF),” 2020. https://towardsdatascience.com/text-vectorization-term-frequency-inverse-document-frequency-tfidf-5a3f9604da6d.
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