ANALISIS SENTIMEN FILM DI TWITTER MENGGUNAKAN METODE SUPPORT VECTOR MACHINE

Abstract

Twitter is one of the social media that is often used to share information or so-called tweets in real time. Based on the results of research in 2013 by Semiocast, a social media research institute, said that the number of Twitter users in Indonesia was third after the United States and Japan with 6.5 percent of users and 1 billion tweets. Tweets can usually influence buying interest, voting for a political figure, or watching their movie. Tweets related to movies become a reference for other Twitter users if they want to watch the same movie. Because there is not service that provides movie references based on other people's comments that are relevant for Indonesian audiences. This study is to analyze the sentiment of tweets on Twitter in the case of Indonesian-language movies that produce movie ratings. The method used for sentiment analysis is the Support Vector Machine (SVM). The final result of this research is a model or SVM algorithm that can classify or analyze film sentiment based on tweets on Twitter by utilizing the Twitter API.