<![CDATA[Good service quality plays an important role in increasing the satisfaction and loyalty of cooperative members. However, challenges in providing optimal service often arise due to limited resources, such as limited number of employees, limited equipment and technology, and lack of training and development. The queue phenomenon is difficult to predict because the arrival time and service time are uncertain. Therefore, a more optimal queue management strategy is needed to reduce waiting time and ensure that service quality is maintained. The research method starts from problem identification, data collection, queue system modeling, to simulation result analysis. The FIFO model-based simulation approach was chosen because it allows testing various scenarios without disrupting company operations. The variables tested in this simulation include waiting time and its average, arrival time, and completion time. This simulation is designed using the Python programming language for flexibility and accuracy in testing queue scenarios. Based on the results of the simulation analysis, it was obtained that the application of the FIFO model provides a clear picture of the waiting time pattern, average waiting time, arrival time, and completion time. The simulation results show that an optimized queue management strategy can significantly reduce waiting time, especially during peak hours. In addition, with this simulation, improvement steps can be identified such as adding employees at certain times, increasing the efficiency of the service process, or using technology to support the automatic queuing system. This study provides strategic recommendations that can be implemented by KUD CV. Rama Investama in improving service quality. The implementation of the simulation results is expected to not only reduce waiting time, but also increase the satisfaction and loyalty of cooperative members, thus supporting the sustainability of overall operations.]]>
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