Subject scheduling is an important element in teaching and learning activities in schools. Scheduling lessons often take a long time due to many factors such as determining teacher teaching hours allocation, the limited number of teachers and teaching in a large number of classes. The problem that often arises is the clash of teaching hours at the same time. One solution to scheduling problems is through the optimization method of Genetic Algorithms. Genetic Algorithms are methods inspired by Mendell's theory of genetics and evolution to solve problems that require optimization. The constraints that were used as constraints in this study were clashing hours of teaching teachers and clashing the same class at the same time. In this study, the results of implementing Genetic Algorithms as a method of optimizing lesson scheduling have not yet obtained optimal results. The solution with the best fitness value is achieved by the number of chromosomes as many as 20, the number of generations is 200, the probability of crossover (Pc) 0.5 and the probability value of mutation (Pm) is from 0.15 to 0.35. The Fastest time for Pm value is 0.15 for 91.22 seconds, while for Pm value of 0.35, it takes 91.65 seconds.