Analyzing and Modelling Pharmacy Queue System Using Simulation

Abstract

Waiting time and queue length at the pharmacy are very influential for customer satisfaction. A hospital's pharmacy which the object of this study has a long waiting time. The aim of this study is to analyzing and modelling pharmacy queue using simulation method, then simulating a new scenario as an effort to improve the queue system. The improvement scenario was simulated by adding one server at payment locket. The simulation was carried out using empirical and theoretical approaches. The analysis was conducted based on the results of the simulation. Results showed that based on validity test can be concluded that the simulation using empirical and theoretical approach do not differ significantly from the real system. Based on the experiment from improvement scenario it showed that the addition of payment server did not show a significant difference from origin situation, the waiting time only decreased by approximately 30 minutes. Journal of Engineering Design and Technology 14considered for improvement at outpatient pharmacy [8] [9][10]. METHODSThis research was conducted using simulation method with theoretical distribution, at both the real system simulation and the proposed improvement scenario simulation. The object of this study was the queuing system at one of hospital's pharmacies in Yogyakarta. Observations were made at the queue system from customers coming to the system until they going home with their drugs. The arrival time of each costumers, waiting time between each process, and service time for each process was recorded to be processed at next step. Observation was done from 7 am-11 am and 14 pm-16 pm. Statistical testing was performed on recorded data to make sure that the data set are enough and there is no outliers.

Service Time Improvement Proposition For Insurance Customer Operation At Bpjs Kesehatan West Bandung Office: A Discrete Event Simulation Approach

“…This component is the basic point to make a simulation of queueing system. The calling population may be assumed to be infinite or finite based on the case [8][9][10][11][12][13][14][15]. verified, validated, experiment design, production runs and analysis, more runs, documentation and reporting, and implementation [3].…”