Teacher Placement using K-Means Clustering and Genetic Algorithm

The problem of teacher placement in a school is faced by Magelang Regency. success determined the minimum total distance between and school, with aim that performance maintained. In computer science this an NP-hard takes very long time to achieve optimal results when done conventional methods. Another approach solve use heuristic algorithms, one which using genetic algorithms. To further improve way narrow search space. study, will be broken down first through clustering process so space becomes narrower, before being subjected algorithm processes. This study cluster original data, placement. method used K-Means while Genetic Algorithm uses Ordered Crossover (OX) operator Partial Shuffle Mutation (PSM) mutation operator. From it was found performing optimization turned out get better than without clustering. 11751 km 9259 km. Also running execute program much shorter (from order hours minutes).