Analysis of eFootball Game User Sentiment Using the Support Vector Machine (SVM) Method

Caca Agustian Caca; April Lia Hananto; Fitria Nurapriani; Baenil Huda

doi:10.59934/jaiea.v4i3.1091

Authors

Caca Agustian Caca Universitas Buana Perjuangan Karawang
April Lia Hananto Universitas Buana Perjuangan Karawang
Fitria Nurapriani Universitas Buana Perjuangan Karawang
Baenil Huda Universitas Buana Perjuangan Karawang

DOI:

https://doi.org/10.59934/jaiea.v4i3.1091

Keywords:

Sentiment analysis, eFootball, Google Play Store, Support Vector Machine, user reviews

Abstract

This study examines the analysis of user review sentiment for eFootball games on the Google Play Store using the Support Vector Machine (SVM) method. A total of 900 reviews written in Indonesian were taken and collected, and divided based on user ratings. The research process includes data exploration, text cleanup (preprocessing), sentiment labeling based on rankings, modeling using SVM, and model evaluation with confusion matrix and accuracy metrics. The results of the analysis showed that the majority of reviews conveyed positive sentiment (48.7%) followed by negative sentiment (44.9%) and neutral sentiment (6.4%). The SVM-based model built in this study achieved an accuracy of 76%, with adequate precision, memory, and F1 scores, especially in the positive and negative sentiment categories. These findings suggest that SVM is effective in classifying digital game review sentiment, but performance in the neutral category requires significant improvement. The study contributes to the use of machine learning to analyze user perceptions of eFootball games and provides recommendations for developers to improve product quality through automated sentiment analysis.

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References

Al Ayyubi, Bahaestie. "Millennial Digital Fiqh: Gacha System in the Online Game Efootball Champion Squads." At-Ta'awun: Journal of Mu'amalah and Islamic Law 2.2 (2023): 230-242.

Ahmad, Kiki. "Analysis of Akulaku and Kredivo Online Loan Sentiment Using the Support Vector Machine (SVM) Method." Journal of Mandalika Literature 4.4 (2023): 323-332.

Atmajaya, Dedy, Annisa Febrianti, and Herdianti Darwis. "SVM and Naive Bayes Method for ChatGPT Sentiment Analysis on Twitter." The Indonesian Journal of Computer Science 12.4 (2023).

Alkindi, Aditia Fikri, and Nurliana Nasution. "Analysis of User Review Sentiment on Roblox Games Using Support Vector Machine and Naive Bayes Methods." J-Com (Journal of Computer) 4.2 (2024): 164-177.

Arrafiq, Muhammad Sunni. "User Sentiment Analysis of Seabank Indonesia's Application Services on Instagram Using the Support Vector Machine Method." Journal of Information System Research (JOSH) 5.4 (2024).

Darwis, Dedi, Eka Shintya Pratiwi, and A. Ferico Octaviansyah Pasaribu. "Application of the SVM Algorithm for Sentiment Analysis on Twitter Data of the Corruption Eradication Commission of the Republic of Indonesia." Journal of Edutic Science: Education and Informatics 7.1 (2020): 1-11

Fide, Sola, Suparti Suparti, and Sudarno Sudarno. "Analysis of tiktok application review sentiment on google play using the support vector machine (svm) and association method." Gaussian Journal 10.3 (2021): 346-358

Fitriyana, Vina, et al. "Sentiment Analysis of Jamsostek Mobile Application Reviews Using the Support Vector Machine Method." Journal of Informatics 14.01 (2023): 40-49.

Gusrananda, Muhammad Raufan. Fanatical and Consumptive Behavior of Online Efootball Game Players. Diss. Islamic University of Indonesia, 2023.

Haris, Muhammad, Aries Suharso, and E. Haodudin Nurkifli. "SENTIMENT ANALYSIS ON EFOOTBALL GAMES ON GOOGLE PLAY STORE USING THE INDOBERT ALGORITHM." JATI (Journal of Informatics Engineering Students) 8.6 (2024): 12108-12121.

Hananto, April Lia, et al. "Digital twins and 3D digital twins: concepts, applications, and challenges in industry 4.0 for digital twins." Computer 13.4 (2024): 100.

Hananto, April Lia, et al. "Elman and Cascade Neural Network with Conjugate Gradient Patterns Restarted to Predict Diesel Engine Performance and Butanol-Triggered Emissions as a Sustainable Biofuel." Engineering Results 19 (2023): 101334.

Hananto, April Lia, et al. "Analysis of drug data mining using the K-Means algorithm." Journal of Physics: Conference Series. Vol. 1908. No. 1. IOP Publishing, 2021.

Haris, Muhammad, Aries Suharso, and E. Haodudin Nurkifli. "SENTIMENT ANALYSIS ON EFOOTBALL GAMES ON GOOGLE PLAY STORE USING THE INDOBERT ALGORITHM." JATI (Journal of Informatics Engineering Students) 8.6 (2024): 12108-12121.

Kusumah, Andika Juda. Analysis of Fiqh Al-Bai' on the buying and selling of players on the eFootball Game application with a Random System. Diss. UIN Sunan Gunung Djati Bandung, 2024.

Lidinillah, Edo Ridho, Tatang Rohana, and Ayu Ratna Juwita. "Analysis of twitter sentiment towards steam using logistic regression algorithm and support vector machine." TECHNOSCIENCE: Journal of Science, Technology and Informatics 10.2 (2023): 154-164.

Mubaroroh, Hindun Habibatul, Hasbi Yasin, and Agus Rusgiyono. "Sentiment Analysis of Ruangguru Application Review Data on Google Play Site Using Naïve Bayes Classifier Algorithm with Normalization of the Word Levenshtein Distance." Gaussian Journal 11.2 (2022): 248-257.

Pamungkas, Adji Surya, and Nuri Cahyono. "Analysis of ChatGPT Review Sentiment on Play Store using Support Vector Machine and K-Nearest Neighbor." Edumatic: Journal of Informatics Education 8.1 (2024): 1-10.

Pangestu, Adhi, Yoseph Tajul Arifin, and Rizky Ade Safitri. "Analysis of Public Review Sentiment of Online Game Users on the Steam Platform Using Naïve Bayes Algorithm." JATI (Journal of Informatics Engineering Students) 7.6 (2023): 3106-3113.

Rahman, Rohim Nur, Abdul Rahim, and Wawan Joko Pranoto. "Sentiment Analysis of eFootball Game Reviews 2024 On Playstore using Naïve Bayes Algorithm." SCIENTIFIC JOURNAL OF INFORMATICS 13.01 (2025): 38-44.

Saputra, Hendi. "Sentiment analysis on booster vaccines using the support vector machine multiclass algorithm on Twitter." Journal of Smart Technology 3.10 (2023).

Syah, Herwin, and Arita Witanti. "Analysis of Public Sentiment Towards Covid-19 Vaccination on Twitter Social Media Using Support Vector Machine (SVM) Algorithm." Journal of Information Systems and Informatics (Simika) 5.1 (2022): 59-67.

Tukino, Tukino, and Fifi Fifi. "Penerapan Support Vector Machine Untuk Analisis Sentimen Pada Layanan Ojek Online." Jurnal Desain Dan Analisis Teknologi 3.2 (2024): 104-113.

Ulfah, Amanny, and Ina Najiah. "Implementation of Web Scraping on the Sinta Journal Site Using the Selenium Webdriver Python Framework." JIKA (Journal of Informatics) 7.1 (2023): 29-36.

Utami, Mar Atul Aji Tyas, Pika Silvianti, and Muhammad Masjkur. "Support Vector Machine Algorithm for Aspect-Based Sentiment Analysis of Mobile Legends: Bang-Bang Online Game Review." Xplore: Journal of Statistics 12.1 (2023): 63-77.