ANALISIS SENTIMEN TERHADAP PEMBELAJARAN DARING DI INDONESIA : Menggunakan Support Vector Machine (SVM) - Alfiyah Nur Indraini (2021)
During this pandemic, a new policy was created in the world of education. The policy encourages students to carry out online learning for a long period of time. The new policy raises a lot of public opinion conveyed through social media. Twitter social media is used as a forum for opinions, one of which is about online learning. Therefore, this study will conduct a sentiment analysis on public opinion regarding online learning in Indonesia to provide information or evaluation of public opinion on Twitter social media. Sentiment analysis can be done by classifying public opinion into positive opinion and negative opinion with the Support Vector Machine (SVM) method. In classifying data, data labeling and data cleaning can be carried out first before going through the text preprocessing process, then the data is given a weight for each word with Term Frequency-Inverse Document Frequency (TF-IDF) which will be used as a feature after that the data is divided using a 10-fold cross. validation and classified by the Support Vector Machine (SVM) method. The average results of the evaluation using the cofussion matrix are accuracy of 0.72 .