ANALISIS SENTIMEN MASYARAKAT TERHADAP PENGGUNAAN VAKSIN COVID-19 DI INDONESIA MENGGUNAKAN METODE NAÏVE BAYES

Leony Martiyana Putri; Yessica Nataliani

Authors

Leony Martiyana Putri Universitas Kristen Satya Wacana
Yessica Nataliani Universitas Kristen Satya Wacana http://orcid.org/0000-0002-5558-7449

Keywords:

COVID-19, vaccination, sentiment analysis, Naïve Bayes

Abstract

COVID-19 was officially declared a global pandemic by WHO on March 11, 2020. In Indonesia, cases of COVID-19 were first detected on March 2, 2020 and there were more and more positive confirmations every day. The government's strategy in fighting this pandemic is by carrying out vaccinations. The use of vaccination has received various responses from the public, both those who support it and those who oppose it. This study aims to analyze public opinion on vaccination, thereby helping the public to see whether vaccines are well received or not. The data used are 600 tweets for three keywords, namely "astra", "sinopharm", and "sinovac", with 200 tweets for each keyword. Each data is divided into 70% training data and 30% testing data. Classification is done using the Naïve Bayes method. Sentiment results with the keyword "astra" show 159 tweets giving neutral sentiment, 19 tweets giving positive sentiment, and 22 tweets giving negative sentiment, with an accuracy of 68,66%. The keyword "sinovac" shows 134 tweets giving neutral sentiment, 13 tweets giving positive sentiment, and 23 tweets giving negative sentiment, with an accuracy of 82,86%. The keyword "sinopharm" shows 77 tweets giving neutral sentiment, 22 tweets giving positive sentiment, and six tweets giving negative sentiment, with an accuracy of 28,77%. It can be concluded that the results of public sentiment towards vaccination received good support from the community.

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