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Analisis Sentimen Model Distilbert Multilingual Cased Dalam Mengklasifikasikan Ulasan Game Genshin Impact Sajad, Abdullah; Nurmalitasari, Nurmalitasari; Purwanto, Eko
CSRID (Computer Science Research and Its Development Journal) Vol. 16 No. 2 (2024): June 2024
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid.16.2.2024.124-136

Abstract

The evolution of information technology has revolutionized how humans engage with the world, particularly within the gaming sector. This paper explores the utilization of the DistilBERT Multilingual Cased model for analyzing sentiments expressed in Genshin Impact game reviews. The research methodology encompasses gathering data from Google PlayStore and Apple AppStore, manually labeling data, preprocessing it, and employing the DistilBERT Multilingual Cased model for analysis. The model's performance is assessed using metrics such as accuracy, precision, recall, and f1-score. Findings reveal that the model effectively categorizes sentiment in reviews, achieving an overall accuracy of 82%. Precision, recall, and f1-score metrics consistently surpass 0.77 across all sentiment categories. This study concludes that the DistilBERT Multilingual Cased model shows promise as a valuable tool for multilingual sentiment analysis within the realm of game reviews.
Co-Authors Adenta Sari, Nur Avia Al Mustofa, Muhammad Hafizh Alliya, Sania Qorrii Atina, Vihi Awang Long, Zalizah Dwi Hartanti Eko Purwanto Hasanah, Herliyani Imam Sujadi JOKO SUSANTO Miftakhul Jannah, Ulfarida Nugroho Arif Sudibyo Nugroho, Mohammad Yusuf Nurchim Nurchim Permatasari, Hanifah Pipin Widyaningsih Rifki Hidayat Sajad, Abdullah Sari, Nur Avia Adenta Setiawati, Neha Poetri Singgih Purnomo Syawaludin, M Ainur Taufik Hidayat Tri Atmojo Kusmayadi Tri Wulandari, Rahmawati Desi Utami, Maulinda Devi