Aulia Kartika
Universitas Islam Negeri Sumatera Utara

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Performance Analysis of Bank Customer Service Queues Using Discrete-Event Simulation with the M/M/1 Model Aulia Kartika; Avin Al-Ghiffari; Suthan Farras Ashar; Syahputri Nanda Wijaya
JITCoS : Journal of Information Technology and Computer System Vol. 2 No. 1 (2026): Journal of Information Technology and Computer System
Publisher : CV. Multimedia Teknologi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65230/jitcos.v2i1.57

Abstract

Fast and efficient service is a crucial element in maintaining customer satisfaction and loyalty to banking institutions. One issue commonly faced by banks is long queues during busy times, which results in increased waiting times and a decline in service quality. The purpose of this study is to examine the performance of the queueing system in bank customer service by utilizing a discrete simulation approach based on the M/M/1 model. This model describes a system with one server, with exponentially distributed arrival and service times, and a random customer arrival rate. In this study, 50 simulations were conducted with variations in arrival rate (λ) and service rate (μ) to gain a comprehensive understanding of the overall system performance. The parameters examined included the average customer waiting time in the queue, the total time customers spent in the system, and the proportion of server utilization. The results of the simulation show that when the arrival rate approaches the service rate (λ → μ), the waiting time increases significantly and the system utilization rate reaches almost 100%. The average customer waiting time was recorded at between 2 and 3 minutes, with a server utilization rate of around 80-85%. In conclusion, the queueing system at banks continues to function well, but there is room for improvement in performance by increasing the number of tellers or improving service times. The findings of this study indicate that discrete simulation can be a powerful tool in analyzing and improving service efficiency for customers in the banking industry.