<![CDATA[Seeing how rapid the development of game industry right now, game developers are required to develop a game that not only have a good feature and graphics but a game that offers a quality conten so that player will play the game. But in a game that have Endless theme, where a game will stop when the player reach a game over, have endless content. If that content is made manually that will consume a lots of time, where that time cost can be used or allocated into other important things such as develop more feature or better graphics in that game. A solution to the problem above is to use Procedural Content Generation(PCG) that is a automatic content generation that done by using an algorithm. PCG is a solution that not only solved the time cost, but also price cost and giving a replayability in a game. The process of making a content, npc or a challenge in an Endless Runner that usually called Enemies is made manually. Enemies that have the same variation makes player bored easily, thus will also reduce replayability factior in the game. With using PCG that uses Genetic Algorithm will solve that problem. In this research, writer will use Genetic Algorithm to implement Procedural Content Generation in 2D Endless Runner Game. Genetic Algorithm is chosen by the writer because it can do optimization that suitable in many cases from an environtment. Beside optimization, Genetic Algorithm is modular, thus separated from the application and can be used in many cases without many changes inside. The result of this testing that is Procedural Content Generation can be applied into 2D Endless Runner Game effectively and efficiently. Whereas the result of the testing can be proved will add positive result in Replayability of the game. In performance side can also be rated positif because in production of an Character every population only need 1-3 seconds compared to creating Non-Player Character manually that cost more time.]]>
