<![CDATA[The rapid growth of the fast-food industry has intensified competition, requiring continuous service quality improvements to maintain customer satisfaction and loyalty. At a popular restaurant, customers often face long queues, with waiting times ranging from 8 to 35 minutes, potentially reducing satisfaction and repeat visits. This study examines the operational conditions of a restaurant that implements a single-channel service system with two process stages: cashier service and food preparation and serving in the kitchen. Observations show that total service time ranges from 8 to 35 minutes, consisting of cashier time of approximately 2–15 minutes and kitchen processing time of 6–20 minutes, with significant variation leading to the formation of long queues. This situation indicates a major bottleneck in the system, particularly in the kitchen during surges in demand, which results in customers leaving the queue before being served and potentially leading to lost revenue. Therefore, this study applies a simulation approach to represent the real conditions of restaurant operations, identify bottlenecks, and evaluate alternative service facility improvements in a structured manner without disrupting operational activities, in order to obtain a more optimal system configuration in terms of waiting time, service capacity, and cost efficiency. This study aims to identify the most suitable queuing model and optimal service facility configuration to reduce both waiting time and queuing costs. Data were collected over three consecutive days through direct observation (1:00 PM–9:00 PM WIB), covering customer arrival, cashier service, food preparation, and order pickup times. Analysis was performed using Arena software supported by distribution testing and scenario simulations. The best improvement scenario involved adding one kitchen station staffed by two employees, reducing the average waiting time from 21 to 13 minutes and achieving a total queuing cost of Rp 227,237.4 per hour. Clarity in cost calculations is necessary so that scenario selection truly reflects the consideration between increasing service capacity and costs that must be borne. However, the lack of explanation regarding the method for assessing customer waiting time costs, assumed labor wage rates, and the basis for calculating operational costs makes the results of the economic analysis difficult to retest and verify. Thus, although the simulation results indicate a decrease in waiting time, the validity of decisions in optimizing service facilities still needs to be supported by a more detailed, measurable, and systematic description of the cost structure. This adjustment resulted in a multi-channel, multi-phase system, enhancing operational efficiency and customer satisfaction. The urgency of this research is important because restaurants experience an imbalance between service capacity and high demand during peak hours. This condition causes long queues and increased customer waiting times. This has an impact on decreased satisfaction and the potential loss of customers who leave the queue. A simulation approach is needed to test various scenarios and determine the most optimal service configuration efficiently.]]>
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