skip to main content

KAJIAN SISTEM ANTRIAN PADA COUNTER KASIR DOMINO’S PIZZA MENGGUNAKAN MEAN VALUE ANALYSIS (STUDI KASUS: DOMINO’S PIZZA GAJAH MADA PEKALONGAN)

*Erin Novela Putri Milenia  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Sugito Sugito  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Tatik Widiharih  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Open Access Copyright 2023 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

Citation Format:
Abstract
Queuing is the phenomenon that occurs when a service needs more than it can handle. This phenomenon is common in many places, such as restaurants. Attempts to analyze the behavior of queuing systems are called queuing system studies, one of which is the use of mean analysis (MVA). MVA can be used when arrival and service times do not follow an exponential distribution. The case study is the queuing system of Domino's Pizza Gajah Mada Pekalongan, which has two counters and took seven days to observe. This study aims to apply MVA and determine performance measures for queuing systems. In this study, MVA can be used because the arrival-to-service time does not follow an exponential distribution. The resulting cue model is (Gamma/GEV/2). (GD/∞/∞) and utilization is 0.43045. The average customer queuing and in the system are at most one customer. The average time to queue is 31.80336 seconds, the average time to complete a service is 321.0971 seconds, and the probability that the system isn’t busy 0.39816 or 39.8%.

Note: This article has supplementary file(s).

Fulltext View|Download |  Research Instrument
CTA Form
Subject
Type Research Instrument
  Download (515KB)    Indexing metadata
Keywords: Domino’s Pizza Gajah Mada Pekalongan; Mean Value Analysis; Queue System

Article Metrics:

  1. Bain, L. J. dan Engelhardt, M. 1992. Introduction To Probability and Mathematical Statistics Second Edition. California: Duxburry Press
  2. Bindu, K. H., Raghava, M., Dey, N., dan Rao, C. R. 2019. Coefficient of Variation and Machine Learning Applications. Boca Raton: CRC Press
  3. Daniel, W. W. 1989. Statistik Nonparametrik Terapan (Terjemahan). Jakarta: PT Gramedia
  4. Fauzia, M. dan Sugito. 2009. Analisis Sistem Antrian Kereta Api di Stasiun Besar Cirebon dan Stasiun Cirebon Prujakan. Jurnal Media Statistika. Vol. 2, No. 2, Hal: 111-120
  5. Gautam, N. 2012. Analysis of Queues: Methods and Applications. Boca Raton: CRC Press
  6. Gross, D., dan Harris, C. M. 1998. Fundamental of Queueing Theory: Third Edition. New York: John Willey and Sons INC
  7. Heizer, J. dan Render, B. 2011. Manajemen Operasi. Edisi Kesembilan. Buku Dua. Jakarta: Salemba Empat
  8. Kakiay, T. J. 2004. Dasar Teori Antrian Untuk Kehidupan Nyata. Yogyakarta: Andi Offset
  9. Khosnevis, B. 1994. Descrate System Simulation. New York: McGraww Hill
  10. Kotz dan Nadarajah. 2000. Extreme Value Distributions Theory and Applications. London: Imperial College Press
  11. Putri, P. A. Kajian Sistem Antrian Dengan Mean Value Analysis pada Pos Entri Data di Stasiun Penerimaan (Studi Kasus Pabrik Gula Kebon Agung). Skripsi. Program Studi Statistika Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Brawijaya
  12. Sugiyono. 2015. Statistika untuk Penelitian. Bandung: Alfabeta
  13. Taha, H. A. 1997. Riset Operasi: Suatu Pengantar. Jakarta: Binarupa Aksara
  14. Walpole, R. 1995. Pengantar Statistika Edisi Ketiga. Jakarta: Gramedia Pustaka Utama
  15. Winston, W. 2004. Operations Research: Applications and Algorithms Fourth Edition. California: Brooks/Cole

Last update:

No citation recorded.

Last update:

No citation recorded.