SENTIMENT ANALYSIS COMPARE LINEAR REGRESSION AND DECISION TREE REGRESSION ALGORITHM TO DETERMINE FILM RATING ACCURACY

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Rivaldo Sitanggang
Daniel Ryan Hamonangan Sitompul
Stiven Hamonangan Sinurat
Ruben, Andreas Situmorang
Denis Jusuf Ziegel
Julfikar Rahmad
Evta Indra

Abstract

Rating assessment in a film is the most important thing because it describes
the satisfaction of film lovers with the films they have watched. With
technological advances like now, we can easily find out the rating of a film
by using a platform to accommodate the audience's review results, namely
the Internet Movie Database (Imdb). The Machune Learning model that has
been created can determine whether the film we watch is good based on
ratings and reviews from moviegoers who share their experiences in
watching similar films. Based on the results of the analysis of the two
algorithms Linear Regression and Dicision Tree Regression, the best
accuracy results from the Decision Tree Regression algorithm are 95.47%

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How to Cite
Sitanggang, R., Sitompul, D. R. H., Sinurat, S. H., Situmorang, R. A., Ziegel, D. J., Rahmad, J., & Indra, E. (2022). SENTIMENT ANALYSIS COMPARE LINEAR REGRESSION AND DECISION TREE REGRESSION ALGORITHM TO DETERMINE FILM RATING ACCURACY. INFOKUM, 10(02), 880-890. Retrieved from http://infor.seaninstitute.org/index.php/infokum/article/view/427

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