Comparison of Naive Bayes and SVM Algorithms for Sentiment Analysis of PUBG Mobile on Google Play Store

Putri Ratna Sari, Dwi Rosa Indah, Errissya Rasywir, Mgs Afriyan firdaus, Ghita Athalina

Abstract


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

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R. J. Santi, D. Setiawa, and I. A. Pratiwi, “Perubahan Tingkah Laku Anak Sekolah Dasar Akibat Game Online,” Jurnal Penelitian dan Pengembangan Pendidikan, vol. 5, no. 3, pp. 385–390, 2021, doi: 10.23887/jppp.v5i3.38576.

S. Irawan and D. S. W., “Faktor-Faktor Yang Mempengaruhi Kecanduan Game Online Peserta Didik,” Jurnal Konseling Gusjigang, vol. 7, no. 1, pp. 9–19, 2021, doi: 10.24176/jkg.v7i1.5646.

B. Kamajaya, “Hubungan Kompetensi Sosial dengan Kecanduan Game Online pada Komunitas Players Unknown’s Battlegrounds (PUBG) Mobile,” Psikoborneo: Jurnal Ilmiah Psikologi, vol. 8, no. 1, pp. 33–39, 2020, doi: 10.30872/psikoborneo.v8i1.

C. Cahyaningtyas, Y. Nataliani, and I. R. Widiasari, “Analisis Sentimen pada Rating Aplikasi Shopee Menggunakan Metode Decision Tree dengan SMOTE,” AITI: Jurnal Teknologi Informasi, vol. 18, no. 2, pp. 173–184, 2021, doi: 10.24246/aiti.v18i2.173-184.

M. Haikal, Martanto, and U. Hayati, “Analisis Sentimen terhadap Penggunaan Aplikasi Game Online PUBG Mobile Menggunakan Algoritma Naive Bayes,” JATI (Jurnal Mahasiswa Teknik Informatika), vol. 7, no. 6, 2023, doi: 10.36040/jati.v7i6.8174.

Y. Firmansyah, R. Kurniawan, and Y. A. Wijaya, “Analisis Data Sentimen Pemain Game Role-Playing Game (RPG) Honkai Star Rail dengan Algoritma Naive Bayes,” Jurnal Informatika dan Rekayasa Perangkat Lunak, vol. 6, no. 1, pp. 127–135, 2024, doi: 10.36499/jinrpl.v6i1.10243.

A. Setiawan and R. R. Suryono, “Analisis Sentimen Ibu Kota Nusantara menggunakan Algoritma Support Vector Machine dan Naïve Bayes,” Edumatic: Jurnal Pendidikan Informatika, vol. 8, no. 1, pp. 183–192, 2024, doi: 10.29408/edumatic.v8i1.25667.

H. Junianto, P. Arsi, B. A. Kusuma, and D. I. S. Saputra, “Evaluasi Aplikasi Raileo Melalui Analisis Sentimen Ulasan Playstore Dengan Metode Naive Bayes,” SINTECH JOURNAL, vol. 7, no. 1, pp. 27–40, 2024, doi: 10.31598/sintechjournal.v7i1.1505.

A. W. V. Hutabarat, N. L. S. S. Adnyani, and K. Suryadi, “Analisis Sentimen Data Ulasan Pengguna MyPertamina di Twitter dengan Metode Machine Learning dan Deep Learning,” Jurnal Rekayasa Sistem Industri, vol. 13, no. 1, pp. 145–154, 2024, doi: 10.26593/jrsi.v13i1.6958.145-154.

A. H. Nurdy, A. Rahim, and Arbansyah, “Analisis Sentimen Ulasan Game Stumble Guys Pada Playstore Menggunakan Algoritma Naïve Bayes Sentiment Analysis of Stumble Guys Game Reviews on Playstore Using the Naïve Bayes Algorithm,” Teknika, vol. 13, no. November, pp. 388–395, 2024, doi: 10.34148/teknika.v13i3.993.

E. R. Kaburuan and N. R. Setiawan, “Sentimen Analisis Review Aplikasi Digital Korlantas Pada Google Play Store Menggunakan Metode SVM,” Jurnal Sisfokom (Sistem Informasi dan Komputer), vol. 12, no. 1, pp. 105–116, 2023, doi: 10.32736/sisfokom.v12i1.1614.

Y. Yu, T. Dinh, F. Yu, and V.-N. Huynh, “Understanding Mobile Game Reviews Through Sentiment Analysis: A Case Study of PUBGm,” Japan Advanced Institute of Science and Technology (JAIST), pp. 102–115, 2023, doi: 10.1007/978-3-031-49333-1_8.

F. I. Wibowo and A. Febriandirza, “Analisis Sentimen Ulasan Pengguna Game Pubg Di Google Play Store Menggunakan Algoritma Naïve Bayes,” Jurnal Sistem Komputer dan Informatika (JSON), vol. 5, no. 3, pp. 590–599, 2024, doi: 10.30865/json.v5i3.7264.

G. P. Permana, D. A. Nugraha, and H. Santoso, “Perbandingan Performa SVM dan Naïve Bayes Pada Analisis Sentimen Aplikasi Game Online,” JOINTECS (Journal of Information Technology and Computer Science), vol. 8, no. 1, pp. 21–30, 2024.

L. B. Ilmawan and M. A. Mude, “Perbandingan Metode Klasifikasi Support Vector Machine dan Naïve Bayes untuk Analisis Sentimen pada Ulasan Tekstual di Google Play Store,” ILKOM Jurnal Ilmiah, vol. 12, no. 2, pp. 154–161, 2020, doi: 10.33096/ilkom.v12i2.597.154-161.

E. S. Romaito, M. K. Anam, Rahmaddeni, and A. N. Ulfah, “Perbandingan Algoritma SVM Dan NBC Dalam Analisa Sentimen Pilkada Pada Twitter,” CSRID Journal, vol. 13, no. 3, pp. 169–179, 2021, doi: 10.22303/csrid.13.3.2021.169-179.

R. Syahputra, G. J. Yanris, and D. Irmayani, “SVM and Naïve Bayes Algorithm Comparison for User Sentiment Analysis on Twitter,” Sinkron : Jurnal dan Penelitian Teknik Informatika, vol. 7, no. 2, pp. 671–678, 2022, doi: 10.33395/sinkron.v7i2.11430.

A. A. Munandar, Farikhin, and C. E. Widodo, “Sentimen Analisis Aplikasi Belajar Online Menggunakan Klasifikasi SVM,” (JOINTECS) Journal of Information Technology and Computer Science, vol. 8, no. 2, pp. 77–84, 2023.

D. Nurmalasari, T. I. Hermanto, and I. M. Nugroho, “Perbandingan Algoritma SVM, KNN dan NBC Terhadap Analisis Sentimen Aplikasi Loan Service,” JURNAL MEDIA INFORMATIKA BUDIDARMA, vol. 7, no. 3, pp. 1521–1530, 2023.

A. Mustolih, P. Arsi, and P. Subarkah, “Sentiment Analysis Motorku X using Applications Naive Bayes Classifier Method,” Indonesian Journal of Artificial Intelligence and Data Mining (IJAIDM), vol. 6, no. 2, pp. 231 – 242, 2023, doi: 10.24014/ijaidm.v6i2.24864.

A. Fauzi and A. H. Yunial, “Analisis Sentimen US Airline Pada Media Sosial Twitter/X Menggunakan Perbandingan Algoritma Data Mining,” JEPIN (Jurnal Edukasi dan Penelitian Informatika), vol. 10, no. 2, pp. 277–286, 2024, doi: 10.26418/jp.v10i2.76024.

O. P. Zusrotun, A. C. Murti, and R. Fiati, “Sentimen Analisis Belajar Online di Twitter Menggunakan Naïve Bayes,” Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI, vol. 11, no. 3, pp. 310–320, 2022, doi: 10.23887/janapati.v11i3.49160.

F. Nufairi, N. Pratiwi, and F. Herlando, “Analisis Sentimen pada Ulasan Aplikasi Threads di Google Play Store Menggunakan Algoritma Support Vector Machine,” JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika), vol. 9, no. 1, pp. 339–348, 2024, doi: 10.29100/jipi.v9i1.4929.

R. Q. Rohmansa, N. Pratiwi, and M. J. Palepa, “Analisis Sentimen Ulasan Pengguna Aplikasi Discord Menggunakan Metode K-Nearest Neighbor,” JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika), vol. 9, no. 1, pp. 368–378, 2024, doi: 10.29100/jipi.v9i1.4943.

A. Hendra and Fitriyani, “Analisis Sentimen Review Halodoc Menggunakan Nai ̈ve Bayes Classifier,” JISKA (Jurnal Informatika Sunan Kalijaga), vol. 6, no. 2, pp. 78–89, 2021, doi: https://doi.org/10.14421/jiska.2021.6.2.78-89.

S. Lestari and S. Saepudin, “Support Vector Machine : Analisis Sentimen Aplikasi Saham di Google Play Store,” JUSIFO (Jurnal Sistem Informasi), vol. 7, no. 2, pp. 81–90, 2021, doi: 10.19109/jusifo.v7i2.9825.

J. J. A. Limbong, I. Sembiring, and K. D. Hartomo, “Analisis Klasifikasi Sentimen Ulasan pada E-Commerce Shopee Berbasis Word Cloud dengan Metode Naive Bayes dan K-Nearest Neighbor,” Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK), vol. 9, no. 2, pp. 347–356, 2022, doi: 10.25126/jtiik.202294960.

B. R. Ansyahry and I. H. Al Amin, “Klasifikasi Opini Masyarakat terhadap Jasa Ekspedisi J&T Express pada Media Sosial Twitter dengan Naïve Bayes,” Jurnal Teknologi Sistem Informasi dan Aplikasi, vol. 6, no. 3, pp. 402–407, 2023, doi: 10.32493/jtsi.v6i3.30878.

A. Syafi’i1, M. Afdal, E. Saputra, and R. Novita, “Analisis Sentimen Ulasan Pengguna Aplikasi Penjualan Pulsa Menggunakan Algoritma Naïve Bayes Classifier,” Jurnal Teknologi Sistem Informasi dan Aplikasi, vol. 7, no. 3, pp. 1300–1308, 2024, doi: 10.32493/jtsi.v7i3.41364.

S. A. Azzahra and A. Wibowo, “Analisis Sentimen Multi-Aspek Berbasis Konversi Ikon Emosi dengan Algoritme Naïve Bayes Untuk Ulasan Wisata Kuliner pada Web Tripadvisor,” Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK), vol. 7, no. 4, pp. 737–744, 2020, doi: 10.25126/jtiik.202071907.

S. Mulya, H. Sujaini, and Tursina, “Analisis Sentimen Tren Olahraga di Masa Pandemi COVID-19 pada Twitter dengan Metode Naïve Bayes Classifier (NBC),” JEPIN (Jurnal Edukasi dan Penelitian Informatika), vol. 8, no. 2, pp. 284–291, 2022, doi: 10.26418/jp.v8i2.52815.

W. Silalahi and A. Hartanto, “Klasifikasi Sentimen Support Vector Machine Berbasis Optimasi Menyambut Pemilu 2024,” Jurnal Riset Sains dan Teknologi, vol. 7, no. 2, pp. 245–255, 2023, doi: 10.30595/jrst.v7i2.18133.

G. R. Ditami, E. F. Ripanti, and H. Sujaini, “Implementasi Support Vector Machine untuk Analisis Sentimen Terhadap Pengaruh Program Promosi Event Belanja pada Marketplace,” JEPIN (Jurnal Edukasi dan Penelitian Informatika), vol. 8, no. 3, pp. 508–516, 2022, doi: 10.26418/jp.v8i3.56478.

S. Khomsah and A. S. Aribowo, “Model Text-Preprocessing Komentar Youtube Dalam Bahasa Indonesia,” Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 4, no. 4, pp. 648 – 654, 2020, doi: 10.29207/resti.v4i4.2035.

A. Rifa’i, H. Sujaini, and D. Prawira, “Sentiment Analysis Objek Wisata Kalimantan Barat Pada Google Maps Menggunakan Metode Naive Bayes,” JEPIN (Jurnal Edukasi dan Penelitian Informatika), vol. 7, no. 3, pp. 400–407, 2021, doi: 10.26418/jp.v7i3.48132.




DOI: https://doi.org/10.32520/stmsi.v13i6.4814

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