<![CDATA[Student course scheduling is a complex challenge in optimizing the utilization of time and educational resources. This research aims to develop a solution for scheduling student subjects using the genetic algorithm method, with a case study at SMPN 03 Penukal. Genetic algorithm is a computational approach that uses the concept of genetic evolution to handle scheduling problems. The study involved collecting data related to class schedules, constraints, and student and teacher preferences. With 29 teachers and 3 classes divided into 9 rooms, as well as 11 subjects covering 40 lesson hours per week, scheduling is very complex. The information gathered was used as input in designing the objective function and basic rules of the genetic algorithm. The genetic evolution process is carried out to find the optimal scheduling solution that meets all the constraints and preferences that have been set. The results showed that the genetic algorithm could produce a schedule with a fitness value of -24 after 230 iterations and 100 individuals, although there were still 24 components that did not fit. The limitation of computer specifications affected this result. This research suggests modification of the fitness function and comparison with other optimization algorithms to improve the efficiency and quality of scheduling.]]>
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