Analisis Sentimen Ulasan Film Oppenheimer Pada Situs Imdb Menggunakan Metode Naive Bayes

Abstract

This research aims to analyze the accuracy of Oppenheimer film sentiment based on audience reviews written via the Internet Movie Database (IMDb) website using the Naive Bayes method. Audience reviews on the IMDb site are a valuable source of information in understanding audience opinions and responses to a film. In this research, researchers implemented the Naive Bayes algorithm classification method to classify reviews as positive or negative sentiment. Movie review data from IMDb is collected and entered into the pre-processing stage, then relevant features are extracted to train the Naive Bayes model. The evaluation results show that the Naive Bayes method can recognize sentiment in Oppenheimer film reviews with a significant level of accuracy. The findings of this research provide valuable insight for the film industry in understanding audience responses to these films, and the sentiment information obtained can be used as a basis for better decision making in film development and marketing. However, researchers acknowledge that there are limitations, especially in classification accuracy in reviews that use ambiguous or unclear language. Therefore, future research could involve other methods or combine several methods to improve the accuracy and reliability of sentiment analysis of film reviews.

Key Words: IMDb, Movie Reviews, Naive Bayes, Sentiment Analysis