<![CDATA[The scheduling of subjects at Dayah Darul Muarrif Al-Aziziyyah is a complex problem due to multiple constraints, such as teacher availability, classroom capacity, and student learning time. This problem falls into the NP-hard category, making conventional methods less effective. This study utilizes a genetic algorithm to efficiently solve the scheduling problem. The schedule is represented as a chromosome containing subject, time, room, and teacher data. Evaluation is performed using a fitness function based on hard constraints (such as schedule conflicts) and soft constraints (such as time preferences). The results demonstrate that the genetic algorithm can produce feasible and more efficient schedules compared to manual scheduling. This study supports the development of adaptive automatic scheduling systems for educational institutions. In addition, the system is designed with a user-friendly interface and is capable of evolving the population iteratively to find an optimal or near-optimal solution. Testing was conducted using real data from Dayah Darul Muarrif Al-Aziziyyah, demonstrating the system’s ability to handle various combinations of constraints with a high degree of accuracy. Thus, this approach not only accelerates the scheduling process but also improves the overall quality of schedule management.]]>
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