Pengaruh Distribusi dan Parameter terhadap Kinerja Sistem Antrian


Authors

  • Mukarramah Yusuf Universitas Hasanuddin, Makassar, Indonesia

DOI:

https://doi.org/10.30865/klik.v3i6.878

Keywords:

Simulation; Discrete Events; Queuing System; Distribution Parameters

Abstract

Discrete event simulation is widely used to evaluate the performance of a queuing system. In those simulations, the data distribution and parameters are determined to approximate the real conditions of the processes that occur in a queuing system. However, the queuing systems with their data distribution and parameters have so far been very specific to a particular system, not general to other systems that run a similar service and own a similar system structure, for example puskesmas, B and C. This research analyzes how much differences the queuing system produces when the system uses different parameters for their data distribution. The analysis is carried out by building the M/M/1 and M/M/2 queue models, then benchmarking several parameters of the exponential distribution and triangular distribution which are used to generate the time lag between arrivals of queue objects and service times. An increase of 60 in the exponential distribution parameter (1 minute patient arrival rate) causes the average number of patients in the queue to decrease by 4 people, and the frequency of large queues to decrease by 5 times. A difference of 0.5 in the triangular distribution parameter (faster service time 0.5 minutes) results in a reduction in waiting time of 0 - 0.2 minutes, and has an impact on the frequency of queues and large queues which can be reduced up to 9 times. Meanwhile, the difference in the number of servers which is one and two on the system can reduce the queue size from 16 to zero

Downloads

Download data is not yet available.

References

Kalwar, M.A., Marri, H.B., Khan, M.A. and Khaskheli, S.A. Applications of queuing theory and discrete event simulation in health care units of Pakistan. International Journal of Science and Engineering Investigations, 10(109), pp.6-18, 2021.

Fun, W.H., Tan, E.H., Khalid, R., Sararaks, S., Tang, K.F., Ab Rahim, I., Md. Sharif, S., Jawahir, S., Sibert, R.M.Y. and Nawawi, M.K.M. Applying Discrete Event Simulation to Reduce Patient Wait Times and Crowding: The Case of a Specialist Outpatient Clinic with Dual Practice System In Healthcare. MDPI, Vol. 10, No. 2, p. 189, Jan 2021.

Shakoor, M., Qureshi, M.R., Jadayil, W.A., Jaber, N. and Al-Nasra, M. Application of discrete event simulation for performance evaluation in private healthcare: The case of a radiology department. International Journal of Healthcare Management, 14(4), pp.1303-1310, 2021.

Shakoor, M., Al-Nasra, M., Abu Jadayil, W., Jaber, N. and Abu Jadayil, S., 2017. Evaluation of provided services at MRI department in a public hospital using discrete event simulation technique: A case study. Cogent Engineering, 4(1), p.1403539.

S. P. Varma, “Waiting Time Reduction in a Local Health Care Centre Using Queueing Theory,” IOSR J. Math., vol. 12, no. 1, pp. 95–100, 2016, doi: 10.9790/5728-121495100

S. K. Mwangi and T. M. Ombuni, “An empirical analysis of queuing model and queuing behaviour in relation to customer satisfaction at Jkuat Students Finance Office,” Am. J. Theor. Appl. Stat., vol. 4, no. 4, pp. 233–246, 2015, doi: 10.11648/j.ajtas.20150404.12.

S. A. Yusuff, “Analysis of Expected, Actual Waiting Time and Service Delivery?: Evidence from Nigeria Banking Industry,” Int. J. Humanit. Soc. Stud., vol. 3, no. 1, pp. 398-402, 2015.

H. A. Haghighinejad et al., “Using Queuing Theory and Simulation Modelling to Reduce Waiting Times in An Iranian Emergency Department,” IJCBNM January, vol. 44, no. 11, pp. 11–26, 2016.

Preston, G.C., Horne, P., Scaparra, M.P. and O’Hanley, J.R, Masterplanning at the Port of Dover: The use of discrete-event simulation in managing road traffic. Sustainability, 12(3), p.1067.2020.

Rusgiyarto, F., Sjafruddin, A., Frazila, R.B. and Suprayogi, S., 2017, June. Discrete event simulation model for external yard choice of import container terminal in a port buffer area. In AIP Conference Proceedings (Vol. 1855, No. 1). AIP Publishing.

Günal, M.M. and Pidd, M. Discrete event simulation for performance modelling in health care: a review of the literature. Journal of Simulation, 4, pp.42-51, 2010.

Zhang, X., 2018. Application of discrete event simulation in health care: a systematic review. BMC health services research, 18(1), pp.1-11.

Santosa, A., Sagathi, M. and Situmorang, M.R. Simulation of First Level Health Care Facilities to Reduce Patient Flow Time. In IOP Conference Series: Materials Science and Engineering Vol. 662, No. 4, p. 042004. IOP Publishing, Nov 2019.

Amelia, P., Lathifah, A., Haq, M.D., Reimann, C.L. and Setiawan, Y. Optimising outpatient pharmacy staffing to minimise patients queue time using discrete event simulation. Journal of Information Systems Engineering and Business Intelligence, 7(2), pp.102-111, 2021.

Yemane, A.M., Heniey, H.A. and Gebrehiwet, K.G. Performance measurement and improvement of healthcare service using discrete event simulation in bahir dar clinic. Journal of Optimization in Industrial Engineering, 14(2), pp.41-51, 2021.

Osais Y. E, Computer Simulation, CRC Press, Florida, 2020.

Python, https://www.python.org/


Bila bermanfaat silahkan share artikel ini

Berikan Komentar Anda terhadap artikel Pengaruh Distribusi dan Parameter terhadap Kinerja Sistem Antrian

Dimensions Badge

ARTICLE HISTORY


Published: 2023-06-24
Abstract View: 0 times
PDF Download: 0 times

How to Cite

Mukarramah Yusuf. (2023). Pengaruh Distribusi dan Parameter terhadap Kinerja Sistem Antrian . KLIK: Kajian Ilmiah Informatika Dan Komputer, 3(6), 780-785. https://doi.org/10.30865/klik.v3i6.878

Issue

Section

Articles