Penerapan Metode Random Forest untuk Prediksi Win Ratio Pemain Player Unknown Battleground
Penerapan Metode Random Forest untuk Prediksi Win Ratio Pemain Player Unknown Battleground
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Penerapan Metode 随机森林和 Prediksi 胜率 Pemain 玩家未知战场
DOI：
10.17605/jmeans.v4i2.545
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Paulina H. Prima Rosa
中科院分区：
文献类型：
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作者：
Reinardus Aji Haristu;Paulina H. Prima Rosa
网络游戏作为电子竞技的一种正在兴起，是未知的战场玩家。要赢得比赛，需要正确的策略。本文通过从kaggle网站上的玩家统计数据中提取数据，对玩家未知战场游戏中的有效策略进行了研究。从统计数据出发，利用随机森林法建立了预测各参与者胜率的模型。从研究结果来看，随机森林能够产生88.19%的准确率。
Online game that is on the rise as one of e-sports is the unknown battleground player. To win the game requires the right strategy. In this paper, a study of effective playing strategies in the player unknown battleground game is explored by extracting data from player statistics taken from the kaggle website. From the statistical data, a model is made to predict the win ratio of each player using the random forest method. From the results of the study, random forest was able to produce an accuracy of 88.19%.