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All Journal MDP Student Conference Jurnal Rekayasa Sistem Informasi dan Teknologi
Orlando, Nikolas
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering

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ANALISIS SENTIMEN KELUHAN PENGGUNA PADA GAME SUPREMACY 1914 MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING Cevin, Jery; Gultom, David; Orlando, Nikolas; Hendrik Fery Herdiatmoko
Jurnal Rekayasa Sistem Informasi dan Teknologi Vol. 2 No. 2 (2024): November
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70248/jrsit.v2i2.1499

Abstract

Penelitian ini bertujuan menganalisis keluhan pengguna untuk pengembangan game Supremacy 1914 dengan memanfaatkan 1000 ulasan berbahasa Indonesia di Google Playstore. Ulasan ini diproses melalui tahapan preprocessing, seperti pemisahan kata (tokenizing), penyaringan (filtering), penghapusan kata tidak penting (stop word), dan pengubahan kata ke bentuk dasar (stemming). Data yang telah diproses dikelompokkan menggunakan metode K-Means menjadi tiga kelompok (cluster), yang divisualisasikan dalam bentuk wordcloud. Cluster 0 mencakup ulasan umum dengan kata-kata seperti "bagus", "seru", dan "mantap", sedangkan Cluster 1 fokus pada masukan terkait kualitas game dan pengalaman pengguna. Penelitian ini diharapkan membantu pengembang mengidentifikasi kebutuhan pengguna lebih cepat, meningkatkan kepuasan, dan mendukung pengembangan game secara berkelanjutan.
Analisis Sentimen Keluhan Pengguna pada Game Mobile Legends Menggunakan Metode K-Means Clustering Orlando, Nikolas; Prasetya, Benedikto Nugroho; Hermawan, Latius
MDP Student Conference Vol 4 No 1 (2025): The 4th MDP Student Conference 2025
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v4i1.11177

Abstract

Mobile Legends is a popular mobile game, but many users express complaints about their gaming experience. This study aims to analyze user complaints’ sentiment using the K-Means Clustering method to group data based on similar complaint patterns. The data was collected from user reviews on the Google Play Store. The results indicate that the K-Means method effectively categorizes complaints into major issues such as connection problems, in-game bugs, and character imbalance. This analysis helps developers identify key user concerns and improve the gaming experience.
Co-Authors Cevin, Jery Gultom, David Hendrik Fery Herdiyatmoko Latius Hermawan Prasetya, Benedikto Nugroho