<![CDATA[The effectiveness of the teaching and learning process within an educational institution is significantly determined by the quality of its course scheduling. The timetable generation process at SMK Darussalam Makassar, which still relies on manual methods using Microsoft Excel, faces several fundamental challenges. This process has been identified as time-consuming (inefficient), leading to delays in the dissemination of the schedule to relevant stakeholders. The primary problem that frequently arises is the occurrence of clashes in teacher schedules, thereby directly disrupting the academic process. To address this scheduling optimization problem, this research implements a Genetic Algorithm. This algorithm is a stochastic search technique inspired by the principles of natural selection and genetics to find optimal or near-optimal solutions. Based on the evaluation results, the developed Genetic Algorithm-based scheduling system demonstrates limitations in terms of scalability. The system only succeeded in achieving an optimal schedule for 56 out of a total of 406 class meetings. This performance limitation is attributed to the architectural and computational resource constraints of the developed platform.]]>
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