Sentiment Analysis of YouTube Movie Trailer Comments Using Naïve Bayes


  • Risky Novendri Department of Information Systems, Telkom University
  • Annisa Syafarani Callista Department of Information Systems, Telkom University
  • Danny Naufal Pratama Department of Information Systems, Telkom University
  • Chika Enggar Puspita Department of Information Systems, Telkom University



Sentiment analysis, Naïve Bayes, Money Heist, Youtube, Opinion Mining


Netflix has produced many TV series, one of which is Money Heist. This series has four seasons with a total of 38 episodes. The fourth season was released on April 3, 2020, which has eight episodes. The fourth season of Money Heist is 31.73 times more demand than the average series around the world. However, despite the many requests for the fourth season of the Money Heist series, there are still some negative comments made by the connoisseurs of the Money Heist series. In the YouTube comments column on the Netflix channel, there are still many who comment neutral and provide positive comments on this series. Therefore, there needs to be a method in which viewers' comments or opinions can be analyzed in order to be able to classify the opinions they make about this series by conducting sentiment analysis using the Naïve Bayes algorithm. Based on the results of research conducted, Naive Bayes can be said to be successful in conducting sentiment analysis because it achieves results of 81%, 74.83%, and 75.22% for accuracy, precision, and recall, respectively.


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How to Cite

Novendri, R., Callista, A. S. ., Pratama, D. N., & Puspita, C. E. . (2020). Sentiment Analysis of YouTube Movie Trailer Comments Using Naïve Bayes. Bulletin of Computer Science and Electrical Engineering, 1(1), 26–32.