Outcome Prediction Using Naïve Bayes Algorithm in The Selection of Role Hero Mobile Legend

Abstract

Abstract According to the e-Marketer market research institute, the net population of the country reached 83.7 million people in 2014. With this amount, Indonesia has been included in the 20 most internet user countries in the world. MOBA is currently in great demand. The high level of competition of this type of MOBA game attracts a lot of game players’ attention to tournaments or competitions officially both regionally and internationally. In 2013 there were around 71.5 million e-Sports enthusiasts around the world. Every year the number of Indonesian gamers is estimated to increase by around 33 percent. With a growth of 33 percent, this certainly makes a great opportunity for game developers. Currently, the games circulating in Indonesia is mostly from foreign countries such as America, Japan, and South Korea. Each hero has a different role (ability). The foresight of players and the ability of individual skills are determined by selecting the composition of hero roles on a team to achieve victory in the legendary mobile gameplay. Naive Bayes Classifier is the simple Statistical Bayesian Classifier. Naive Bayes is able to classify role heroes well enough to predict the victory based on the role hero chosen by the player. Naïve Bayes implementation can explore the characteristics of the attribute and dataset of the chosen role hero. Naïve Bayes algorithm method can predict the Victory in mobile legend gameplay from existing hero roles based on datasets and training data.