Analisis Sentimen Vaksinasi Booster Covid-19 pada Platform Twitter Menggunakan Metode Naïve Bayes

Dessy Tri Anggraeni


Since the end of 2019, the Covid-19 virus hit the whole world, including in Indonesia. One of the efforts to deal with the Covid-19 virus is vaccination. In Indonesia, the government requires people to vaccinate 3 times, that are  First Vaccination, Second Vaccination, and Booster Vaccination. The public's response to the booster vaccine are varies. This study aims to reveal public sentiment towards booster vaccine activities. The research was conducted by collecting tweet data from the Twitter platform. The research was conducted by collecting data tweets from Twitter. The method used is the Naïve Bayes Classifier because the method is simple, the process is fast, and it has a fairly high level of confidence. In this method, public sentiment is divided into three, that are positive, neutral, and negative. The results showed that most people responded positively to this booster vaccine activity with a value of 56.8%, neutral as much as 39.9%, and negative as much as 3.3% with an accuracy rate of 86%.


Classification; Covid-19; Naïve Bayes Classifier; Sentiment; Twitter

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