Twitter is a social networking site that has a large user base. On Twitter, users may interact and talk about concepts and events. Social media usage is growing, which opens up new opportunities to study various communication aspects and trends. One of these is social media analysis, which has the specific goal of analyzing data to generate information. Twitter may be used to gain a thorough picture of current events and significant trends, such as how the Indonesian government handled the COVID-19 outbreak. Since the year 2020 began, COVID-19 has spread over the globe. The most recent information and viewpoints about the coronavirus are presented by various people, including media organizations and governmental bodies. In this study, tweet data was extracted from Twitter using the python programming language. After undergoing a number of pre-processing steps to clean up the data and get it ready for feature extraction, sentiment analysis, and classification, including positive sentiment, negative sentiment, and neutral sentiment using the Naïve Bayes algorithm, the data was then used in the study. The hashtag term "omicron" was used to collect data from Twitter. The three-week data search period runs from February 7 until February 27, 2022. A total of 106,834 pieces of data were successfully extracted from Twitter. The findings of the data analysis show that negative attitudes account for up to 46.44% of the total.