<![CDATA[Efficient course scheduling is a critical task for academic institutions to ensure optimal use of resources and minimize conflicts. This paper presents the implementation of a Genetic Algorithm (GA) in the development of a web-based course scheduling information system at the Faculty of Computer and Multimedia, UNIKI. The primary objective is to create a robust scheduling system that addresses common scheduling challenges such as overlapping classes, uneven distribution of course loads, and room availability. The Genetic Algorithm is utilized due to its effectiveness in solving complex optimization problems. The algorithm's selection, crossover, and mutation processes are tailored to the unique requirements of course scheduling. The system is designed to generate feasible and near-optimal schedules by iteratively improving a population of potential solutions. Preliminary results indicate that the GA-based scheduling system significantly reduces scheduling conflicts by 95% and enhances the overall scheduling process compared to traditional methods. Classroom utilization improved, with an average occupancy rate of 85%, and user satisfaction increased by 80% due to the intuitive user interface and time-saving automated process. These results demonstrate the potential of Genetic Algorithms to streamline academic scheduling, making it a valuable tool for educational institutions.]]>
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