Film Review Sentiment Analysis Using TF-IDF and Support Vector Machine
Abstract
Abstract— With today's technological advancements, all information about all movies is readily available on the Internet. If information is managed properly, it can provide benefits in the form of useful information to help individuals or organizations to make decisions. This study aims to explain sentiment analysis on film documents. The methods used in this research are TF-IDF (Term Frequency-Inverse Document Frequency) and SVM (Support Vector Machine). This method was chosen because it is capable of weighting words and classifying high-dimensional data. From the scenario tests conducted, it is known that the TF-IDF and SVM algorithms can be used for film review cases with an Accuracy value of 85%, a Precision value of 100%, a Recall value of 70%, and an F1-Score value of 82%.
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Copyright (c) 2022 Okta Ihza Gifari, Muh. Adha, Fernandito Freddy, Fernandito Freddy Setlight Durrand
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