Analisis Sentimen Tanggapan Masyarakat Terhadap Vaksin Covid-19 Menggunakan Algoritma Support Vector Machine (SVM) - Layla Qodary Zalyhaty; Vivine Nurcahyawati; Erwin Sutomo (Jurnal Sistem Informasi dan Komputerisasi Akuntansi (JSIKA), 2022)
The COVID-19 outbreak has had a significant impact on health and economic sectors. The Government has been working to solve the problems, one of which is by procuring the COVID-19 vaccine.  The provision of COVID-19 vaccine aims to reduce the transmission of coronavirus, lower the rate of pain and death, achieve herd immunity. But in the midst of the birth of the COVID-19 vaccine, there are pros and cons in the community. Some support vaccines, and others doubt the effectiveness and efficacy of the COVID-19 vaccine. Some of them even rejected vaccines even though the government gave vaccines for free.  The public gave their responses and opinions in various media. One of the media that is always  updated about various developments is online news. Online news contains responses and public opinion both negative and positive related to a topic. In order for vaccination to run optimally, the government needs to consider various inputs, among others, by looking at how the response and public opinion to the vaccination discourse,so that the government can evaluate and determine the next strategy related to education and socialization about the COVID-19 vaccine to    the  community. The result of evaluation F1 score is 88.37%,  accuracy score 82.76%, precision score 79.17%, and  recall 100%. Pie chart shows the percentage result of positive sentiment worth 70% and negative worth 30% of the overall data.