<![CDATA[Scheduling is one of the most needed requirement for high school. Scheduling at brawijaya smart school senior high school(BSS SHS) had some problems like processing time, schedule size, Musyawarah Guru Mata Pelajaran(MGMP), and managing variety subjects. Scheduling took 3 days to be done. Problem space's size is 834 hours of subject. Teacher's schedule cannot crashed with MGMP. Variations of teachers and subjects cannot be the same within a day from those problems above researcher will use genetic algorithm to solve them. Genetic algorithm is an algorithm that can be used to get the solution that closed to optimum from the wide possibility solution area. In this research, researcher used partially-mapped crossover, reciprocal exchange mutation, and elitism selection. The result gets that the 233rd generation, 150 population size, 0,7 crossover ratio, and 0,3 mutation ratio are the most optimum solution parameter in BSS SHS scheduling case. This research has its disadvantage in early convergence that happened at 233rd generation so random injection is needed to be applied. Global and local search aren't effective because searching ratio is always the same. Population size was too big that difficults the searching for the best parent so parent selection needed to be applied.]]>
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