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

Rivaldo Sitanggang (Universitas Prima Indonesia)
Daniel Ryan Hamonangan Sitompul (Universitas Prima Indonesia)
Stiven Hamonangan Sinurat (Universitas Prima Indonesia)
Ruben, Andreas Situmorang (Universitas Prima Indonesia)
Denis Jusuf Ziegel (Universitas Prima Indonesia)
Julfikar Rahmad (Universitas Prima Indonesia)
Evta Indra (Universitas Prima Indonesia)

INFOKUM
Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence

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%