Transformasi Ulasan Game menjadi Insight Strategis menggunakan Aspect-Based Sentiment Analysis dan Business Intelligence

Abstract

Video games were initially developed in military environments as a form of entertainment and have since evolved into a global industry with billions of players. One of the popular RPG games is Elden Ring, which generates a large volume of user reviews, making it difficult for developers to effectively identify praise and complaints. This study aims to perform ABSA on player reviews, covering gameplay, graphics, performance, and story, while also comparing the performance of LR, BERT, and RF, and visualizing the results through a BI dashboard. The results indicate that all aspects are dominated by positive sentiment. BERT achieved the highest accuracy at 90%, followed by LR (89%) and RF (83%), although LR demonstrated more stable confidence values. The visualization further reveals that positive sentiments are more consistent, whereas negative sentiments tend to be more complex and diverse. For future research, it is recommended to apply model calibration techniques, including softmax output calibration, incorporating uncertainty into the training process, and evaluating calibration using Expected Calibration Error to improve alignment between confidence and actual model performance.