Sentiment Analysis Against Political Figure’s Billboard During Pandemic Using Naïve Bayes Algorithm

In the midst of Covid-19 Pandemic, many Indonesians have reacted negatively to placement political individuals' billboards with very huge sizes on streets. The early campaign that was run thought be contentious. On social media like Twitter, majority people freely share their thoughts. purpose this study is investigate how general public advertising figures during epidemic and categorize those responses. It envisaged it would also provide advice for connected parties may used when making judgments regarding policy constructing a pandemic based results data analysis. Twitter users tend more expressive because character limits, which means they sentimental or emotional values. Using Nave Bayes Algorithm, possible do sentiment analysis by categorizing user comments into positive, negative, neutral attitudes. Regarding sentiments expressed showing leaders pandemic, tweets were sorted three categories: liked, unfavorable, neutral. accuracy rate from Naive categorization personalities 83.3% precision value 89%, recall 83%, f-1 score 82%.