SUMMARY
The game is a field of science is growing rapidly and very interesting to learn because review has potential good view of science and commercial aspect. To produce an attractive and realistic games, there are a few things to note. One of them is the attention to the attack strategy, especially for the NPC (Non Player Character). Referring to previous studies that discuss strategies melee attack for NPC (Non Player Character)[1]. This study combines two Collision Detection with Bayesian methods for attacking strategy melee. In this study is to divide some of the behavior of NPCs attack when in the position closest to the enemy. This study applies the algorithm for Bayesian classification assault NPC behavior and collision detection algorithms for decision-making behavior when NPCs hit the player. By merging algorithm aims to improve on the weaknesses of previous research. NPC assault classification is divided into two offensive behavior: attitudes and behavior kick smash. As for the variables used in Bayesian classification is health points, attack points player and the distance obtained from NPC conditions. The results of the implementation of collision detection and Bayesian methods have proved that the collision detection methods can take decisions NPC attack behavior although placed closest to the player. From the test results with the calculation methods confusion matrix gain as much as 90% accuracy.