A Analysis and Modeling Simulation King Kuphi Cafe Queuing System With Customer Arrival Variations Using Python

Abstract

Queueing system modeling and simulation is an effective approach for analyzing service performance in business environments with dynamic customer arrival rates, such as at King Kuphi Cafe. This study aims to model the queueing system at the cafe with various variations in customer arrival rates using the queueing theory approach and simulate it using the Python programming language. The models used are the M/M/1 and M/M/c queueing systems, which allow analysis of changes in waiting time, queue length, server utilization, and service level based on variations in arrival (λ) and service (μ) parameters. The simulation was run using Python packages such as NumPy and SimPy to represent the arrival and service processes realistically. The results of the study show that an increase in the rate of customer arrivals significantly affects system performance, particularly in terms of an increase in average waiting time and queue length. In addition, adding more servers has been proven to reduce queue congestion and improve overall service quality. These findings are expected to serve as a basis for King Kuphi Cafe managers in making strategic decisions regarding the number of baristas and operational optimization to achieve more efficient service.