Modeling and simulation of queuing system for customer service improvement: A case study

Xian, Tan Chai; Hong, Chai Weng; Hawari, Nurul Nazihah

doi:10.1063/1.4966087

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…The service sectors problem, especially at the hypermarket relates a lot with the insufficient checkout FGIC2019 system provided, which will lead to longer waiting time among customers. This situation will bring to customer dissatisfaction and frustration (Xian et al, 2016). There are several processes for the customers to complete the buying processes which are choosing the checkout system, get into the checkout system, cashiers scanning and placing all the items in bags and make a payment before leaving.…”

Section: Discussionmentioning

confidence: 99%

“…The previous study conducted by Xian et al (2016) examined the service performance, which will affect customer satisfaction. In the study, they aimed to help the management to improve service performance by developing a simulation model.…”

Section: Simulation Studies For Queuing Problemmentioning

confidence: 99%

“…Karnon et al (2012) verifying that DES is a form of computerbased modeling that provides an intuitive and flexible approach to representing complex systems. DES also as a tool for analyzing the service performance that gives an impact on customer satisfaction (Xian, Hong, & Hawari, 2016).…”

Section: Introductionmentioning

confidence: 99%

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Application of Discrete Event Simulation (DES) for Queuing System Improvement at Hypermarket

Mohamad

Saharin

2019

KSS

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This paper focuses on the development of a computer simulation model for improving the queuing system at a hypermarket using Discrete Event Simulation (DES) and to propose the most efficient hypermarket queuing system for overall improvement. Data were collected from the Hypermarket A using the time study. The method of this study is using modeling and simulation. Arena Simulation Software is used to develop the model to replicate the actual system. Three scenarios had been tested, and the alternatives will be ranked based on the level of the efficiency of the system performance. The most efficient queuing system is identified based on the scenario analysis. In this study, the waiting time for each customer can be improved by up to 26%, which equivalent to 5.24 minutes. Overall, this study contributes to a better understanding of the queuing system performance.

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Section: Discussionmentioning

confidence: 99%

Section: Simulation Studies For Queuing Problemmentioning

confidence: 99%

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Application of Discrete Event Simulation (DES) for Queuing System Improvement at Hypermarket

Mohamad

Saharin

2019

KSS

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“…Simulasi telah menjadi suatu hal yang sangat penting pada manajemen operasi [5] [6]. Salah satu masalah yang dapat diselesaikan dengan menggunakan simulasi salah satunya adalah masalah antrian [7]. Berbagai penelitian dan kajian dilakukan dengan menggunakan metode simulasi sebagai salah satu teknik untuk memecahkan masalah [8]- [10].…”

Section: Pendahuluanunclassified

Simulasi Usulan Perbaikan Sistem Antrian di Bank XYZ

Aqidawati,

Nugraha

2023

waluyojatmiko

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Simulasi telah menjadi suatu hal yang sangat penting pada manajemen operasi. Salah satu masalah yang dapat diselesaikan dengan menggunakan simulasi salah satunya adalah masalah antrian. Permasalahan yang ada pada sistem antrian Bank XYZ adalah penumpukan antrian di kursi tunggu dan lamanya waktu pelayanan teller sehingga kurang efisien bagi customer. Penelitian ini bertujuan untuk melakukan simulasi sistem antrian di bank tersebut, sehingga dapat disusun usulan perbaikan bagi sistem antrian ini. Simulasi antrian ini dibuat dengan menggunakan software Arena. Beberapa data dikumpulkan melalui pengamatan langsung untuk membuat model antrian awal. Model simulasi antrian yang disusun dapat memberikan informasi mengenai rata – rata waktu antrian pelanggan, sehingga dapat disusun sebuah usulan perbaikan berupa pengelompokan antrian berdasarkan jenis transaksi di sistem tersebut. Kata Kunci: Arena, Simulasi, Sistem Antrian.

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“…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].…”

Section: Simulation Of Queueing Systemmentioning

confidence: 99%

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

Utami Sri Hajarismala,

Wasesa

2023

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BPJS Kesehatan is one of the public legal entities in Indonesia and provides public services to the public, one of which is the administration process service and the provision of face-to-face information directly to the nearest BPJS Kesehatan office. The Customer Satisfaction Index is an assessment of whether the services provided by BPJS Kesehatan are in accordance with participants' expectations. To create excellent service for participants, BPJS Kesehatan refers to 5 dimensions of service quality, namely Tangibility, Empathy, Responsiveness, Reliability, and Assurance. One of the face-to-face service problems faced by BPJS Kesehatan West Bandung Office every day is the waiting time and long queues. This problem was even listed on the Customer Satisfaction Index as one of the participants' dissatisfaction points. To find out what causes long queues and the long waiting time for participants, interviews, and observations of conditions in the field are needed. This can be searched in a structured manner using Fishbone Analysis. To help find solutions to these problems, we use Discrete Event Simulation in the Anylogic application to analyze the existing service conditions and find alternative solutions to solve the issue. As a result, we propose several alternative operational scenarios and define the best scenario that can be applied to increase CSI and reduce participant complaints about waiting times and long queues.

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Modeling and simulation of queuing system for customer service improvement: A case study

Cited by 7 publications

References 8 publications

Application of Discrete Event Simulation (DES) for Queuing System Improvement at Hypermarket

Application of Discrete Event Simulation (DES) for Queuing System Improvement at Hypermarket

Simulasi Usulan Perbaikan Sistem Antrian di Bank XYZ

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

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