Analisis Sentimen Komentar Youtube Mengenai Vaksin Covid-19 Menggunakan Support Vector Machine

Abstract

Vaccination is one of the policies taken by the Indonesia government to control the Covid-19 pandemic. Vaccination is expected to form community immunity to prevent the spread of Covid-19. This policy taken by the government has generated various responses from the public in the form of opinions posted on social media platforms, one of which is on the Youtube. In order to better understand public sentiment towards this vaccination policy, it is necessary to analyze the opinions given. The Support Vector Machine (SVM) algorithm used in this study to classify public sentiment on vaccination policy. The data sources used are comments posted on Youtube videos regarding Covid-19 vaccinations. Three scenarios were used in the test with variations in the ratio of the testing data and training data of 90:10, 80:20, and 70:30 with 10 tests on each variation of the data ratio. Based on the tests carried out, the results obtained accuracy of 86%, 85%, and 84%.