Analysis of Public Sentiment on Covid-19 Vaccination Policy Based on Text Mining with The Naïve Bayes Classifier Approach

Abstract

One of the goals in the SDGs, which is to ensure a healthy life and promote the welfare of all people of all ages, has become difficult to maintain since the emergence of Covid-19 in Indonesia. Thus, the Indonesian government has issued a policy regarding the procurement of vaccines and the implementation of vaccinations through Presidential Regulation Number 99 of 2020. Meanwhile, the public's perception of the Covid-19 vaccine that appears are varies and will affect the Covid-19 vaccination process in Indonesia, so a sentiment analysis needs to be carried out to free Indonesia from the Covid-19 pandemic. By using the text mining method, the primary data collected is in the form of public opinions from Twitter. With the Naïve Bayes Classifier approach, it is concluded that the model is consistent and good enough to be used to classify public sentiment regarding the Covid-19 vaccination policy.