Social media is a place to look for new friends and a place to express opinions about something freely. One social media that is widely used today is Twitter. Many people use Twitter to issue opinions on the Covid-19 Pandemic that occurred in various countries, including in Indonesia. The Covid-19 pandemic or coronavirus in Indonesia begins with the discovery of a 2019 coronavirus sufferer (COVID-19) on March 2, 2020, to April 8, 2020, 2,738 positive cases of COVID-19 have been confirmed, with 221 cases of which have died and 204 cases have recovered. Tweets written by the public can later be classified into positive and negative sentiments using sentiment analysis. The results of our sentiment analysis can see how the perceptions of the Indonesian people regarding the Covid-19 pandemic that occurred in Indonesia. The sentiment analysis classification process will use the naïve Bayes method. Sentiment testing carried out using Cross-Validation includes 5 Fold and 10 Fold testing. From each of these tests, the accuracy, precision, and recall values will be seen. the results of the Cross Validation 5 Fold test obtained results from an average accuracy of 0.756364 (75%). The results of the Cross Validation test for 10 Fold obtained results from an average accuracy of 0.76 (76%)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
The writer agreed that the article copyright by Smatika journal and the writer has the right to disseminate the paper published without permission in advance.
 M. Bouazizi and T. Ohtsuki, “Sarcasm detection in twitter: »all your products are incredibly amazing!!!» - are they really?,” in 2015 IEEE Global Communications Conference, GLOBECOM 2015, 2015, doi: 10.1109/GLOCOM.2014.7417640.
 M. Arnani, “2.738 Orang Positif Covid-19 di Indonesia, Ini Rincian Kasus di 32 Provinsi,” Kompas, Jakarta, 2020.
 G. A. Buntoro, “Analisis Sentimen Calon Presiden Indonesia 2014 Dengan Lima Class Attribute,” Universitas Gadjah Mada, 2015.
 A. Faisal, Y. Alkhalifi, A. Rifai, and W. Gata, “Analisis Sentimen Dewan Perwakilan Rakyat Dengan Algoritma Klasifikasi Berbasis Particle Swarm Optimization,” JOINTECS (Journal Inf. Technol. Comput. Sci., vol. 5, no. 2, p. 61, 2020, doi: 10.31328/jointecs.v5i2.1362.
 C. D. Manning, P. Ragahvan, and H. Schutze, “An Introduction to Information Retrieval,” Inf. Retr. Boston., no. c, pp. 1–18, 2009, doi: 10.1109/LPT.2009.2020494.
 T. A. M, Y. Alkhalifi, N. A. Mayangky, and W. Gata, “Analisis Sentimen Opini Publik Mengenai Larangan Mudik pada Twitter Menggunakan Naive Bayes,” CoreIT, vol. 6, no. 2. 2020.
 D. A. Putri, D. A. Kristiyanti, E. Indrayuni, A. Nurhadi, and D. R. Hadinata, “Comparison of Naive Bayes Algorithm and Support Vector Machine using PSO Feature Selection for Sentiment Analysis on E-Wallet Review,” J. Phys. Conf. Ser., vol. 1641, no. 1, 2020, doi: 10.1088/1742-6596/1641/1/012085.
 M. Habibi, “Analisis Sentimen Dan Klasifikasi Komentar Mahasiswa Pada Sistem Evaluasi Pembelajaran Menggunakan Kombinasi Knn Berbasis Cosine Similarity Dan Supervised Model,” Universitas Gadjah Mada, 2017.