Analisis Sentimen Masyarakat Indonesia terhadap Covid-19 pada Media Sosial Twitter menggunakan Metode Naive Bayes - Tuahta Ramadhani; Yuita Arum Sari; Edy Santoso (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2021)
Twitter is often used by users to write or discuss issues and various topics that are currently happening. Twitter, which has many active users, is able to create a Twitter trending topic, where people are able to freely share information as well as the latest opinions on issues that are being discussed internationally. Not only as a liaison for socializing and interacting, Twitter can be used as a means of giving hope and showing about many things that are happening also in the community, such as in the case of the Covid-19 pandemic in Indonesia. With the emergence of the Covid-19 pandemic, it has caused various opinions from citizens, especially on Twitter social media users, especially the Indonesian people. Information about the views of residents is conveyed very quickly. there are those who defend and disagree regarding the information regarding the emergence of the Covid-19 pandemic. Everyone has their own thoughts and opinions, therefore this sentiment analysis can be applied to find out people's opinions on events that occur. In addition, in this study, sentiment analysis can be used to determine the level of accuracy based on data comments or opinions contained on Twitter social media. This study uses a classification strategy based on the Naive Bayes algorithm to classify text into three classes, namely positive, negative, and neutral. The use of this algorithm is also because it is a simple method. The difference between this study and previous research is the object of research which focuses on tweet comments related to Covid-19. From this study, it can be concluded that the results of the sentiment analysis system using the Naive Bayes method for Covid-19 data on Twitter and the level of accuracy with the Confusion Matrix are 87%.