Practicum course scheduling is a complex task in higher education institutions as it involves multiple parameters such as lecturer availability, room capacity, and time slots. This process poses a significant challenge for laboratory administrators in ensuring that scheduling conflicts are avoided and that all resources are utilized optimally. This study implements a Genetic Algorithm (GA) to optimize the practicum course scheduling process at STMIK AMIKOM Yogyakarta, which has since been renamed Universitas Amikom Yogyakarta. The methodological stages include population initialization, fitness evaluation, selection using the Roulette Wheel Selection method, crossover using One Point Crossover, and mutation using Targeted Mutation. The results demonstrate that the genetic algorithm successfully produces optimal solutions by eliminating lecturer and room conflicts, while also maximizing equitable time utilization. During the iteration phase, the algorithm generated a conflict-free practicum schedule with a maximum fitness value of 167. The process terminated at the first generation after identifying two optimal chromosomes out of ten. These findings confirm that the genetic algorithm is effective in solving practicum scheduling problems and can be applied to minimize schedule clashes and improve operational efficiency in academic environments.