Twitter User Sentiment Analysis of the Sinovac (Covid-19) Vaccine Using the Naïve Bayes Method
Keywords:
Sentiment Analysis, Vaccine Sinovac, Naive Bayes, Classification, Confusion MatrixAbstract
In 2020 Indonesia became one of the countries affected by this corona virus. The government has made various efforts to suppress the spread of the corona virus, one of which is by taking vaccinations. The existence of this vaccination, of course, received a response from the community. Many opinions that appear ranging from hopes to worries. One of the forums where the public can express themselves is through the social network Twitter. In the process of processing public opinion data from Twitter social media, a preprocessing process is needed which can then be classified. The method used to analyze public opinion on Covid-19 vaccination is Naive Bayes. The results of the analysis of public sentiment on the Sinovac vaccine using the Naive Bayes method on Twitter showed that of the 1,139 tweet data, 82% were positive and 18% were negative, so it can be concluded that public sentiment tends to be positive. With accuracy or model testing with Confusion Matrix and K Fold Validation, data accuracy is 80%.
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