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All Journal International Journal of Engineering, Science and Information Technology International Journal of Community Service
Benny Mutiara, Achmad
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Sentiment Analysis of Honkai: Star Rail Indonesian Language Reviews on Google Play Store Using Bidirectional Encoder Representations from Transformers Method Fitra Ramadhan, Zekri; Benny Mutiara, Achmad
International Journal of Engineering, Science and Information Technology Vol 3, No 3 (2023)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v3i3.462

Abstract

Online games are a type of entertainment that is done by humans to have fun and forget all the problems in everyday life. Honkai: Star Rail is a new online game application owned by miHoYo which is currently popular and widely downloaded on the Google Play Store. Reviews on the Honkai: Star Rail app are increasing over time so this makes it difficult for app developers to know past user reviews on their apps. Therefore, the author conducted a study to analyze sentiment towards Honkai: Star Rail application reviews in Indonesian on the Google Play Store using the Bidirectional Encoder Representations from Transformers (BERT) method to determine user sentiment towards the Honkai: Star Rail application and then processed further so that it becomes a record for developers, users, and prospective users of the Honkai: Star Rail application. This study uses Indonesian language review data from users of the Honkai: Star Rail application found on the Google Play Store website as many as 6000 reviews. The BERT method applied in this study consisted of data collection, dataset labeling, data preprocessing, dataset splitting, modeling, model training, and evaluation. Based on the evaluation results that have been carried out on the test data, 97 data are true positive with 27 data are false positive, 4 data are true neutral with 47 data are false neutral, and 381 data are true negative with 37 data are false negative. So, it can be concluded that the model still has difficulty predicting reviews with neutral sentiment but is good enough at predicting reviews with positive and negative sentiment. In addition, the accuracy of the model is 81% with a precision of 63% for positive sentiment reviews, 36% for neutral sentiment reviews, and 89% for negative sentiment reviews.
Strengthening Partnership : ICT Academy APTIKOM - HUAWEI Tiawan, Tiawan; Benny Mutiara, Achmad; Rayi Pradono Iswara; Teja, Husni; Solikin, Solikin; Anggraini, Yunita; Ismiyati, Ismiyati; Aripiyanto, Saepul; Ariesta, Eliza; Surjandy, Surjandy; Gusan Putra, Merios; Suryana, Radit; Lukman Hakim, Dani; Atsirina Krisnaputri, Nilam; Supam Wijaya, Arif; Agung, Mulya
International Journal Of Community Service Vol. 5 No. 4 (2025): November 2025 ( Indonesia - Thailand - Malaysia - Timor Leste - Philippines )
Publisher : CV. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijcs.v5i4.932

Abstract

Through strategic cooperation between university and industry, the community service initiative "Strengthening Partnership: ICT Academy APTIKOM–Huawei" seeks to establish a long-lasting digital talent ecosystem in Indonesia. The initiative, which is being implemented under the APTIKOM network with active participation from Institut Teknologi Sains Bandung (ITSB), incorporates curriculum alignment, structured talent development pathways, and worldwide ICT certification. By connecting academic learning with real-world technical standards and enabling instructors and students to gain globally recognized competencies, the program fosters innovation in higher education. The collaboration supports the development of human capital in a sustainable manner that is in line with Golden Indonesia 2045 and Indonesia's national digital transformation strategy. Regarding global development alignment, this initiative directly promotes SDGs 17 (Partnerships for the Goals) through cross-sectoral engagement between universities, professional associations, and the ICT industry, and SDG 4 (Quality Education) through ICT-driven capacity building. The results show that collaboration-driven innovation can increase equal access to technology education across Indonesian higher education institutions, boost institutional capabilities, and speed up digital preparedness.
Co-Authors Anggraini, Yunita Ariesta, Eliza Aripiyanto, Saepul Atsirina Krisnaputri, Nilam Fitra Ramadhan, Zekri Gusan Putra, Merios Ismiyati, Ismiyati Mulya Agung, Mulya Rayi Pradono Iswara Solikin Solikin Supam Wijaya, Arif Surjandy, Surjandy Suryana, Radit Teja, Husni Tiawan, Tiawan