Practical scheduling is the process of preparation of an implementation schedule that informs a number of courses, lecturers who teach, space, and time of lecture activities in the laboratory. It should be noted several aspects to arrange lecture schedule in accordance with the needs. Aspects that need to be considered include aspects of lecturers who teach, courses taught. Manual scheduling tends to take longer and enough accuracy for the schedule maker. To be able to create an optional schedule, an optimization method is required. In this research, will be tested the optimization method in the preparation of the practice schedule that is Genetic Algorithm. Genetic algorithms are a computational approach to solving problems modeled by biological processes of evolution. The parameters of the Genetic Algorithm affecting the course schedule are the number of individuals, the probability of crossover, the probability of mutation and the method of selection, the crossover used. Testing is done by finding the most optimal parameter values of genetic algorithm in lecture schedule. The results show that with the number of generations, the number of individuals, the probability of crossover and the probability of mutation can produce the most optimal schedule.