SENTIMENT ANALYSIS OF MERDEKA BELAJAR KAMPUS MERDEKA POLICY USING SUPPORT VECTOR MACHINE WITH WORD2VEC - Rezki, Nurul; Thamrin, Sri Astuti; Siswanto, Siswanto (PATTIMURA UNIVERSITY, 2023)
Sentiment analysis is a data text analysis that classifies data into positive and negative sentiments. This study aims to obtain the results of sentiment classification related to Merdeka Belajar Kampus Merdeka policy on Twitter using support vector machine algorithm with Word2Vec feature extraction. Support Vector Machine is a classification algorithm that separates data classes using the optimum hyperplane. Text data used in sentiment analysis must change its numerical form by performing feature extraction. In this study, the feature extraction used is Word2Vec which represents words in vector form. Data in this study are tweets with the keyword