Application of Naive Bayes Algorithm for Analysis of User Reviews on Mobile Legends Game: Bang Bang
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Abstract
Mobile Legends: Bang Bang is a highly popular MOBA game, especially among students, which generates a large volume of user reviews on the Google Play Store. These reviews provide a valuable data source for understanding user sentiment. This study conducts sentiment analysis on user reviews using three variants of the Naïve Bayes algorithm: BernoulliNB, GaussianNB, and MultinomialNB. From an initial 5,000 reviews collected via web scraping using Python, 4,428 reviews were used after neutral reviews were removed to focus solely on positive and negative sentiments.The preprocessing steps included case folding, word normalization, tokenization, stopword removal, and stemming. Sentiment labeling was carried out using a lexicon-based approach, comparing the frequency of positive and negative words in each review. The dataset was split in an 80:20 ratio for training and testing.The results show that MultinomialNB achieved the highest accuracy at 75%, followed by BernoulliNB with 74%, and GaussianNB with 50%. MultinomialNB demonstrated superior performance in detecting positive sentiments, while BernoulliNB offered more balanced results. GaussianNB performed poorly due to its assumption of normally distributed continuous data, which is unsuitable for text classification. This study concludes that Multinomial Naïve Bayes is the most effective model for sentiment analysis of user reviews when working with word frequency-based representations.
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References
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[23] D. Ramadhani, D. Fadel, Bintang A. Nugroho, "User Sentiment Analysis Towards the Whatsapp Application on the Google Play Platform Using the Natural Language Processing Method," Journal of Computer Science (JIK) Volume 8, Number 1, March 2025: 39-49 E-ISSN: 2746-7163,
[24] M. Z. Siregar, A. M. Elhanafi, D. Irwan, "Sentiment analysis of social media application reviews on Google Play using the naïve bayes algorithm," JATI (Informatics Engineering Student Journal) Vol. 9 No. 2, April 2025, doi: https://doi.org/10.36040/jati.v9i2.12841
[2] N. Khesya,” Get to know flowcharts and pseudocodes in algorithms and programming”, vol 1 des 2021 doi; https://doi.org/10.31219/osf.io/dq45e
[3] D. Normawati, S. A. Prayogi, "Implementation of Naïve Bayes classifier and confusion matrix on text-based sentiment analysis of twitter tada," Journal of Computer Science & Informatics (J-SAKTI) Volume 5 Number 2, September 2021, pp. 697-711 ISSN: 2548-9771/EISSN: 2549-7200,him:http://dx.doi.org/10.30645/j-sakti.v5i2.369
[4] A. Yusnita, S. Lailiyah, K. Saumahudi, "Application of the naïve bayes algorithm for the acceptance of new education participants," WICIDA informatics Vol.10 No.1(2021): January 2021,doi: https://doi.org/10.46984/inf-wcd.1194
[5] M. Y. Putra and D. I. Putri,” Utilization of Naïve Bayes Algorithm and K-Nearest Neighbor for Classification of Majors of Grade XI Students,” Jurnal TEKNO KOMPAK, Vol. 16, No. 2, P-ISSN: 1412-9663, E-ISSN: 2656-3525, Pages 176-187, 2022, doi: https://doi.org/10.33365/jtk.v16i2.2002
[6] N. Agustina,D. H. Citra, W. Purnama, C. Nisa, A. R. Kurnia,” The Implementation of Naïve Bayes Algorithm for Sentiment Analysis of Shopee Reviews on Google Play Store," Indonesian Research and Publication Institute (IRPI) MALCOM:, Indonesian Journal of Machine Learning and Computer Science Journal Homepage: Vol. 2, Iss. 1 April 2022, pp: 47-54P-ISSN: 2797-2313 ISSN(E): 2775-8575, doi: https://journal.irpi.or.id/index.php/malcom
[7] A. I. Tanggraeni, M. N. N. Sitokdana, "Sentiment Analysis of E-Government Applications on Google Play Using the Naïve Bayes Algorithm," Journal of Informatics Engineering and Information Systems ISSN 2407-4322 Vol. 9, No. 2, June 2022, Pages 785-795 E-ISSN 2503-2933
[8] M. N. Rahman, “Performance analysis of the use of stopwords and stemming in sentiment analysis with the naive bayes classification approach,”Institutional Repository of Syarif Hidayatullah State Islamic University,2-Nov-2022 doi: https://repository.uinjkt.ac.id/dspace/handle/123456789/65210
[9] S. A. Rizaldi, S. Alam, I. Kurniawan, "Sentiment analysis of JMO (Jamsostek Mobile) application users on the Google Play Store using the naive bayes method," STORAGE - Scientific Journal of Engineering and Computer Science, Vol. 2No. 3, August 2023,109-117e-ISSN: 2828-5344, doi: 10.55123
[10] C. G. Indrayanto, D. E. Ratnawati2, B. Rahayudi, “Sentiment analysis of user review data of mypertaminadi indonesia application on google play store using random forest method,” Journal of Information Technology and Computer Science Development-ISSN: 2548-964XVol. 7, No. 3, March 2023, pp. 1131-1139, doi: http://j-ptiik.ub.ac.id
[11] D. Rifaldi, A. Fadlil, Herman, "Preprocessing Techniques in Text Mining Using Mrntal Health Tweet Data," DECODE: Journal of Information Technology Education ISSN Print: 2775-2984 | ISSN Online: 2775-1813 Vol. 3, No. 2, September 2023, Pages: 161-171, Doi: http://dx.doi.org/10.51454/decode.v3i2.131
[12] K. D. Indarwati, H. Februaryyanti,Sentiment Analysis of Gojek Application Service Quality UsingKDNaive Bayes Classifier Method”,JATISI, March 2023, Volume: 10 Number: 1 doi: https://doi.org/10.35957/jatisi.v10i1.2643
[13] J. .A. Rieuwpassa, Sugito, T. Widiharih, "Implementation of the naïve bayes classifier method for classifying sentiments of Netflix user reviews on Google Play," GAUSSIAN JOURNAL, Volume 12, Number 3, Year 2023, Pages 362-371, ISSN: 2339-2541, doi: https://ejournal3.undip.ac.id/index.php/gaussian/
[14] S. Bayulianto, I. Purnamasari, M. Jajuli,”Prediction of the winning rate of the Mobile Legends Professional League Indonesia Season 9 using the Naive Bayes algorithm”,JIPI (Scientific Journal of Informatics Research and Learning), Vol. 8, No. 2, June 2023, Pp. 538-55,doi: https://doi.org/10.29100/jipi.v8i2.3562
[15] D. Wijaya, R. A. Saputra, F. Irwiensyah, "Sentiment Analysis of National Digital Samsat Application Reviews on Google Playstore Using the Naïve Bayes Algorithm," KLIK: Scientific Study of Informatics and Computers ISSN 2723-3898 (Online Media) Vol 4, No 4, February 2024, Pages 2369-2380 DOI 10.30865/klik.v4i4.1738
[16] T. R. P. Hermawan, A. R. Dzikrillah, "Application of Naïve Bayes Method for Sentiment Analysis on ChatGPT Application User Reviews on Google Play Store." Building of Informatics, Technology and Science (BITS) Volume 6, No 1, June 2024 Page: 430-439 ISSN 2684-8910 (print media) ISSN 2685-3310 (online media) DOI 10.47065/bits.v6i1.5400
[17] A. D. A. S. Surya, Y. Yamasari, “Application of Naïve Bayes (NB) Algorithm for Heart Disease Classification,” JINACS: Volume 05 Number 03, 2024 (Journal of Informatics and Computer Science), ISSN: 2686-2220, doi: 10.26740/jinacs.v5n03.p447-455
[18] I. B. Setiawan, J. Maulindar, Nurchim, “Application of naïve bayes algorithm for sentiment analysis in digital health applications,” G-Tech: Jurnal Teknologi Terapan Vol. 8, No. 4, October 2024, pp. 2301-2312 E-ISSN: 2623-064X | P-ISSN: 2580-8737,doi: https://doi.org/10.70609/gtech.v8i4.5020
[19] A. F. N. Aziza, V. P. Ramadhan, “Comparison of Naïve Bayes and K-NN in Sentiment Analysis on Twitter Regarding the Victory of Candidate Pair 02, vol 12 no 2 2024 J-INTECH(journal of information and technology, doi: https://doi.org/10.32664/j-intech.v12i02.1305
[20] N. Z. B. Jannah, Kusnawi,” Comparison of Naïve Bayes and SVM in Sentiment Analysis of Product Reviews on Marketplaces, vol 8 no 2 2024 Sinkron (jurnal& penelitian Informatika, DOI: 10.33395/sinkron.v8i2.13559
[21] R. I. Agustin,” Comparison of naïve bayes and SVM Algorithms Umyuk Twitter Sentiment Analysis of Corruption of Rice Social Assistance during Pandemic Period’’,vol 12 no.2 2024 doi: https://doi.org/10.23960/jitet.v12i2.4020
[22] H. Firda, P. Putra, N. R. Oktadini, P. E, Sevtiyuni,” Comparison of Rating-based and Inset Lexicon-based Labeling in Sentiment Analysis Using SVM (Case Study: GoBiz Application Review on Google Play Store), Sistemasi: Jurnal Sistem Informasi Volume 14, Number 2, 2025: 516-528 ISSN:2302-8149 e-ISSN:2540-9719 doi: http://repository.unsri.ac.id/id/eprint/166015
[23] D. Ramadhani, D. Fadel, Bintang A. Nugroho, "User Sentiment Analysis Towards the Whatsapp Application on the Google Play Platform Using the Natural Language Processing Method," Journal of Computer Science (JIK) Volume 8, Number 1, March 2025: 39-49 E-ISSN: 2746-7163,
[24] M. Z. Siregar, A. M. Elhanafi, D. Irwan, "Sentiment analysis of social media application reviews on Google Play using the naïve bayes algorithm," JATI (Informatics Engineering Student Journal) Vol. 9 No. 2, April 2025, doi: https://doi.org/10.36040/jati.v9i2.12841