Comparison of Support Vector Machine and XGBSVM in Analyzing Public Opinion on Covid-19 Vaccination

Abstract

The coronavirus has become a global pandemic and has spread almost all over the world, including Indonesia. The spread of COVID-19 in Indonesia causes many negative impacts. Therefore, the government took vaccination measures to suppress the spread of COVID-19. The public's response to vaccination was quite diverse on Twitter, some were supportive, and some were not. The data used in this study came from Twitter which was taken using the emprit drone portal by using the keyword, "vaccination." The classification is conducted using the SVM and hybrid methods between SVM and XGBoost or what is commonly called XGBSVM. The purpose of this study is to provide an overview to the public on whether the Covid-19 vaccination tends to create positive, neutral, or negative opinions. The results of the sentiment evaluation show that SVM has