<![CDATA[Employee shift scheduling in the Micro, Small, and Medium Enterprises (MSMEs) sector is a complex problem because it must consider various aspects such as workforce availability, work hour restrictions, and individual preferences. At the Nasi Balap Cucun MSME which operates in the culinary field, the challenge is even greater because most of its employees are active students with diverse class schedules. The scheduling process is still done manually often takes a long time and results in an unbalanced division of labor. To overcome this, this study developed an automatic scheduling system based on Genetic Algorithms combined with Constraint Satisfaction Problems (CSP). The system was built using the Python programming language with the DEAP library, considering shift needs, employee schedule requests, and operational constraints. The implementation results show that the system is able to generate efficient weekly schedules with an increase in time efficiency of up to 80%. After testing the system, it was found that the scheduling results would appear less than 10 seconds after the user generated the schedule. In addition, the system showed an increase in fitness value from -1000 in the initial generation to 54 in the 50th generation, which means this system is able to reduce potential conflicts in scheduling. This approach can be an effective solution for MSMEs in optimizing human resource management intelligently.]]>
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