MOBA GAME REVIEW SENTIMENT ANALYSIS USING SUPPORT VECTOR MACHINE ALGORITHM

Alif Fajar Panjalu, Syariful Alam, Mochammad Imam Sulistyo

Abstract


MOBA as one of the many popular subgenres today, Mobile Legend, Arena of Valor, League of Legend and Lokapala based on the large number of downloads can be mentioned as popular MOBA games, but the rating of these four applications is below 4.0 on the Google Play platform Store, this happens because some users may think that this mobile MOBA game has several advantages, but also some disadvantages that affect ratings. This study aims to determine the results of sentiment analysis on mobile MOBA games using Google Play Store reviews. Then it is processed using Python programming to create a model with the linear kernel Support Vector Machine (SVM) algorithm to classify the dataset. From the results of the classification model test using 19,579 data, where there were 10,017 positive sentiment data and 9,562 negative sentiment data and the distribution of train data and test data was 70%: 30%, obtained an accuracy of 82.64% and then re-evaluated using the Cross Validation method using 5 times so that an accuracy of 83.38% is obtained

 

Keywords: MOBA, Sentiment Analysis, Machine Learning, SVM, Cross Validation


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DOI: https://doi.org/10.33387/jiko.v6i2.6388

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