Comparison of Naive Bayes and SVM Algorithms for Sentiment Analysis of PUBG Mobile on Google Play Store
PlayerUnknown's Battlegrounds (PUBG) Mobile is one of the most popular mobile games in Indonesia, according to data from the Google Play Store. According to the Google Play Store, the game has a rating of 3.8 with 49.5 million reviews. While a considerable number of users express satisfaction,...
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| Format: | Article |
| Language: | Indonesian |
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Islamic University of Indragiri
2024-11-01
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| Series: | Sistemasi: Jurnal Sistem Informasi |
| Online Access: | https://sistemasi.ftik.unisi.ac.id/index.php/stmsi/article/view/4814 |
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| author | Putri Ratna Sari Dwi Rosa Indah Errissya Rasywir Mgs Afriyan firdaus Ghita Athalina |
| author_facet | Putri Ratna Sari Dwi Rosa Indah Errissya Rasywir Mgs Afriyan firdaus Ghita Athalina |
| author_sort | Putri Ratna Sari |
| collection | DOAJ |
| description | PlayerUnknown's Battlegrounds (PUBG) Mobile is one of the most popular mobile games in Indonesia, according to data from the Google Play Store. According to the Google Play Store, the game has a rating of 3.8 with 49.5 million reviews. While a considerable number of users express satisfaction, a significant proportion of reviews also contain criticism regarding the gameplay and features. However, a cursory examination of reviews may not fully capture the nuances of user sentiment, necessitating a more comprehensive sentiment analysis. This research will employ a positive and negative sentiment analysis of Indonesian PUBG Mobile reviews on the Google Play Store, utilizing a comparative approach to evaluate the performance of two algorithms: Naïve Bayes and Support Vector Machine (SVM). The data set comprised 2,000 user reviews, which were collected using a scraping technique. Following this, a labeling process was conducted based on the rating, data were preprocessed, TF-IDF weighting was applied, and both algorithms were implemented. The findings indicated that users expressed satisfaction with the game's visuals and gameplay. However, there were also technical concerns that required attention, including bugs, server instability, lag, and performance issues. The SVM algorithm demonstrated superior performance, with an accuracy rate of 70.95%, compared to Naïve Bayes, which reached 69.83%. Despite Naïve Bayes's faster processing speed, SVM exhibited greater precision, recall, and F1-score |
| format | Article |
| id | doaj-art-b86892fedca34ccfbdff7904e7a85988 |
| institution | Kabale University |
| issn | 2302-8149 2540-9719 |
| language | Indonesian |
| publishDate | 2024-11-01 |
| publisher | Islamic University of Indragiri |
| record_format | Article |
| series | Sistemasi: Jurnal Sistem Informasi |
| spelling | doaj-art-b86892fedca34ccfbdff7904e7a859882025-01-08T03:10:27ZindIslamic University of IndragiriSistemasi: Jurnal Sistem Informasi2302-81492540-97192024-11-011362767277910.32520/stmsi.v13i6.4814929Comparison of Naive Bayes and SVM Algorithms for Sentiment Analysis of PUBG Mobile on Google Play StorePutri Ratna Sari0Dwi Rosa Indah1Errissya Rasywir2Mgs Afriyan firdaus3Ghita Athalina4Universitas SriwijayaUniversitas SriwijayaUniversitas Dinamika Bangsa Jambi.Universitas SriwijayaUniversitas SriwijayaPlayerUnknown's Battlegrounds (PUBG) Mobile is one of the most popular mobile games in Indonesia, according to data from the Google Play Store. According to the Google Play Store, the game has a rating of 3.8 with 49.5 million reviews. While a considerable number of users express satisfaction, a significant proportion of reviews also contain criticism regarding the gameplay and features. However, a cursory examination of reviews may not fully capture the nuances of user sentiment, necessitating a more comprehensive sentiment analysis. This research will employ a positive and negative sentiment analysis of Indonesian PUBG Mobile reviews on the Google Play Store, utilizing a comparative approach to evaluate the performance of two algorithms: Naïve Bayes and Support Vector Machine (SVM). The data set comprised 2,000 user reviews, which were collected using a scraping technique. Following this, a labeling process was conducted based on the rating, data were preprocessed, TF-IDF weighting was applied, and both algorithms were implemented. The findings indicated that users expressed satisfaction with the game's visuals and gameplay. However, there were also technical concerns that required attention, including bugs, server instability, lag, and performance issues. The SVM algorithm demonstrated superior performance, with an accuracy rate of 70.95%, compared to Naïve Bayes, which reached 69.83%. Despite Naïve Bayes's faster processing speed, SVM exhibited greater precision, recall, and F1-scorehttps://sistemasi.ftik.unisi.ac.id/index.php/stmsi/article/view/4814 |
| spellingShingle | Putri Ratna Sari Dwi Rosa Indah Errissya Rasywir Mgs Afriyan firdaus Ghita Athalina Comparison of Naive Bayes and SVM Algorithms for Sentiment Analysis of PUBG Mobile on Google Play Store Sistemasi: Jurnal Sistem Informasi |
| title | Comparison of Naive Bayes and SVM Algorithms for Sentiment Analysis of PUBG Mobile on Google Play Store |
| title_full | Comparison of Naive Bayes and SVM Algorithms for Sentiment Analysis of PUBG Mobile on Google Play Store |
| title_fullStr | Comparison of Naive Bayes and SVM Algorithms for Sentiment Analysis of PUBG Mobile on Google Play Store |
| title_full_unstemmed | Comparison of Naive Bayes and SVM Algorithms for Sentiment Analysis of PUBG Mobile on Google Play Store |
| title_short | Comparison of Naive Bayes and SVM Algorithms for Sentiment Analysis of PUBG Mobile on Google Play Store |
| title_sort | comparison of naive bayes and svm algorithms for sentiment analysis of pubg mobile on google play store |
| url | https://sistemasi.ftik.unisi.ac.id/index.php/stmsi/article/view/4814 |
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