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All Journal Xplore: Journal of Statistics
Mar Atul Aji Tyas Utami
Department of Statistics, IPB University, Indonesia
Decision Sciences, Operations Research & Management Engineering Mathematics

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Algoritme Support Vector Machine untuk Analisis Sentimen Berbasis Aspek Ulasan Game Online Mobile Legends: Bang-Bang Mar Atul Aji Tyas Utami; Pika Silvianti; Muhammad Masjkur
Xplore: Journal of Statistics Vol. 12 No. 1 (2023): Vol. 12 No. 1 (2023)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (905.151 KB) | DOI: 10.29244/xplore.v12i1.1064

Abstract

The presence of the digital technology era is facilitated by an internet connection that is easily accessible and provides many features and entertainment, one of which is online games. Mobile Legends: Bang-Bang is a Multiplayer Online Battle Arena (MOBA)-type online game that has been popular since its launch in 2016. Currently, Mobile Legends: Bang-Bang is still the top free game on the Google Play Store. This popularity is inseparable from user reviews that provide different information and sentiment. This research will identify the sentiment of application user reviews based on aspects of gameplay, performance, visualization, and player. The classification method used in this study is the Support Vector Machine (SVM). The online game application Mobile Legends: Bang-Bang tends to have negative sentiment from aspects of gameplay, performance, and player. However, from the visualization aspect, they tend to have positive sentiment. The results of the evaluation of the model based on the value of accuracy, F1-score, and AUC, it was found that the gameplay, Performance, and Player aspects gave better classification results than the Visualization aspect.
Co-Authors Muhammad Masjkur Pika Silvianti