OPTIMIZATION OF PLAYERS AND GAME WIN PREDICTION USING NAÏVE BAYES ALGORITHM
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Abstract
Mobile Legends Bang Bang has developed into one of the most popular mobile games. It has even been competed in the SEA Games 2021 Vietnam through esports. Many players are trying to take part in the race but have not achieved maximum results. The influencing factors include the composition of the team and the heroes used. This study aims to calculate the prediction of victory and the composition of a team through specialty, role, and counter heroes using the nave Bayes algorithm and apply it to matches so that the hope of victory can be achieved.
The use of parameters for calculating the probability of winning is calculated using the nave Bayes formula P(X|Ci) = P(x1|Ci) . P(x2|Ci) . P(x3|Ci) . P(x4|Ci) where each variable represents the total victory or defeat, the total winrate of the specialty hero in one team, the type of role hero used, and the presence or absence of the opposing team's counter hero in the allied team.
The test results obtained, the specialty winrate has an effect of 91%, the type of role has an influence of 86%, and the counter hero has an effect of 60%, and for the win rate, the results obtained are 40 times from a total of 50 matches, which means this application has an accuracy of 80 %.
The use of parameters for calculating the probability of winning is calculated using the nave Bayes formula P(X|Ci) = P(x1|Ci) . P(x2|Ci) . P(x3|Ci) . P(x4|Ci) where each variable represents the total victory or defeat, the total winrate of the specialty hero in one team, the type of role hero used, and the presence or absence of the opposing team's counter hero in the allied team.
The test results obtained, the specialty winrate has an effect of 91%, the type of role has an influence of 86%, and the counter hero has an effect of 60%, and for the win rate, the results obtained are 40 times from a total of 50 matches, which means this application has an accuracy of 80 %.
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Dharmawan, A. (2022). OPTIMIZATION OF PLAYERS AND GAME WIN PREDICTION USING NAÏVE BAYES ALGORITHM. Electro Luceat, 8(1), 36-47. https://doi.org/10.32531/jelekn.v8i1.447
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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
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[5] D. L. Olson and D. Delen, Advanced data mining techniques, no. January. 2008.
[6] M. K. Han Jiawei, Data Mining Concepts and Techniques, 3rd editio. Waltham: Morgan Kaufmann, 2012.
[7] I. Sommerville, Software Engineering, 9th Editio. Boston: Pearson Education, Inc, 2011.
[8] Y. Lianawati, “SISTEM INFORMASI SIMPAN PINJAM BERBASIS WEBSITE PADA KOPERASI SIMPAN PINJAM ‘BETA KARINA JAYA’ di CILACAP,” JELC, vol. 7, no. 2, 2021.
[9] M. S. A.S Rosa, Rekayasa Perangkat Lunak Terstruktur dan Berorientasi Objek, Revisi. Bandung: Informatika, 2018.
[10] Munawar, Analisis Perancangan Sistem Berorientasi Objek Dengan UML. Bandung: Informatika, 2018.