SUMMARY
Scheduling lectures at academic institutions especially the Faculty of Engineering and Information Technology General Achmad Yani University Yogyakarta is still done semi-manually with the help of Microsoft Excel and takes days to determine the days and space and hours of lectures, while in making schedules must be done optimally and fast because the schedule will be used for lecture activities each semester. In preparing lecture scheduling, it can be done by applying methods that are often used. One of them is using a genetic algorithm which is one of the right algorithms to solve complex search and optimization problems. Genetic algorithms can find the best solution from a broad set of candidates and have many optimum points. In other words, genetic algorithms provide solutions to scheduling problems to minimize collision schedules with coding stages, determine initial population values, determine chromosome values at random, determine fitness values for minimize the broken schedule, then select the roulette wheel, cross-move one-point crossover, then perform value coding mutations. This research is expected to be able to contribute knowledge about the application of genetic algorithms to overcome problems in the scheduling field