Building of Informatics, Technology and Science
Vol 4 No 1 (2022): Juni 2022

Implementation Naïve Bayes Classification for Sentiment Analysis on Internet Movie Database

Samsir Samsir (Universitas Al Washliyah Labuhanbatu, Rantauprapat)
Kusmanto Kusmanto (Universitas Al Washliyah Labuhanbatu, Rantauprapat)
Abdul Hakim Dalimunthe (Universitas Al Washliyah Labuhanbatu, Rantauprapat)
Rahmad Aditiya (Teknik Informatika, Universitas Al-Washliyah Labuhanbatu)
Ronal Watrianthos (Universitas Al Washliyah Labuhanbatu, Rantauprapat)



Article Info

Publish Date
27 Jun 2022

Abstract

A film review is a subjective opinion of someone who has different feelings about each film. As a result, film enthusiasts will struggle to assess whether the film meets their requirements. Based on these issues, sentiment analysis is the best way to fix them. Sentiment analysis, also known as opinion mining, is the study of assigning views or emotional labels to texts in order to determine if the text contains positive or negative thoughts. The Nave Bayes method was chosen because it can classify data based on the computation of each class's probability against objects in a given data sample. The best model was created utilizing data without lemmatization, 500 vector sizes, and Nave Bayes classification, with an accuracy of 78.96 percent and a f1-score of 78.81 percent. Changes in vector size affect the system's capacity to foresee positive and negative sentiments. The difference in accuracy and recall values shows that when vector size 300 is utilized, the precision and recall outcomes are lower than when vector size 500 is used.

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Journal Info

Abbrev

bits

Publisher

Subject

Computer Science & IT

Description

Building of Informatics, Technology and Science (BITS) is an open access media in publishing scientific articles that contain the results of research in information technology and computers. Paper that enters this journal will be checked for plagiarism and peer-rewiew first to maintain its quality. ...