Analysis of Public Sentiment on Vaccination in Efforts to Overcome the Covid-19 Pandemic
Abstract
Coronavirus has become a global pandemic and has spread almost all over the world, including Indonesia. Many negative impacts resulted from the spread of COVID-19 in Indonesia, so the government made vaccination measures to reduce the rate of spread of COVID-19. Responses from the public to vaccination measures are quite diverse on social media Twitter. Some are supportive and some disagree. The purpose of this study is to find out how people's sentiment towards vaccination measures. The data used 845 tweets, using two keywords, "vaksinmerahputih" and "vaksinsinovac." The data is then divided into 253 training data and 592 testing data. The classification will use the SVM and Naïve Bayes methods. The classification result of the Naïve Bayes method received an average accuracy of 85.59%, while SMV of 84.41%. Sentiment results on Naïve Bayes method with keyword "vaksinsinovac" gets positive sentiment of 66% and negative sentiment of 34%, while "vaksinmerahputih" obtains 89% and 11% for positive and negative sentiment, respectively. SVM method with keyword "vaksinsinovac" gets 96% positive and 4% negative, while "vaksinmerahputih" obtains 98% positive and 2% negative. It can be concluded that the results of public sentiment towards vaccination measures received a positive response.
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