SENTIMENT ANALYSIS ON TWITTER OF PSBB EFFECT USING MACHINE LEARNING - Irwansyah Saputra; Jose Andrean Halomoan; Adam Bagusmugi Raharjo; Cyra Rezky Ananda Syavira (Lembaga Penelitian dan Pengabdian Pada Masyarakat, 2020)
A collection of tweets from Twitter users about PSBB can be used as sentiment analysis. The data obtained is processed using data mining techniques (data mining), in which there is a process of mining the text, tokenize, transformation, classification, stem, etc. Then calculated into three different algorithms to be compared, the algorithm used is the Decision Tree, K-NN, and Naïve Bayes Classifier to find the best accuracy. Rapidminer application is also used to facilitate writers in processing data. The highest results from this study were the Decision Tree algorithm with an accuracy of 83.3%, precision 79%, and recall 87.17%.