Service Waiting Time Behavior of Express Maintenance (EM) Program of PT. Dunia Barusa Banda Aceh

Authors

  • Samsul Anwar Syiah Kuala University http://orcid.org/0000-0003-3165-2151
  • Tri Wahyudi Syiah Kuala University
  • Mutia Andriani Syiah Kuala University
  • Dinda Maulina Syiah Kuala University
  • Juraida Fitri Syiah Kuala University
  • Raihan Nora Syiah Kuala University
  • Zulfazli Zulfazli Syiah Kuala University

DOI:

https://doi.org/10.20956/jmsk.v16i3.4927

Keywords:

CDF, express maintenance (EM), PDF, service waiting time, survival and hazard function

Abstract

Survival analysis is a statistical method that can be used to analyze duration time data of an event occurrence. This research uses secondary data from PT. Dunia Barusa branch Banda Aceh that collected from January to March 2017 which amounted to 107 data. The data is service waiting time (in minutes) of Express Maintenance (EM) program on sub section receptionist, service, final inspection, confirmation, technical complete, invoicing, customer notification and delivery. There are 4 functions analyzed, namely density probability function (PDF), cumulative distribution function (CDF), survival and hazard function. The study shows that the probability of a customer being in the waiting process of service tends to become smaller as the service waiting time become longer on each sub section of the EM program, as well as the probability to remain in the waiting process after the customer has been there within a certain period of time indicated by the survival function. The hazard function shows that the rate of a customer will be served instantaneously in the sub section receptionist, service, invoicing, customer notification and delivery changing over the time, while in the sub section of final inspection, technical complete and confirmation, the rates are constant over the time as high as 0.757, 0.794, and 3.336 respectively.

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Author Biographies

Samsul Anwar, Syiah Kuala University

Department of Statistics

Tri Wahyudi, Syiah Kuala University

Department of Statistics

Mutia Andriani, Syiah Kuala University

Department of Statistics

Dinda Maulina, Syiah Kuala University

Department of Statistics

Juraida Fitri, Syiah Kuala University

Department of Statistics

Raihan Nora, Syiah Kuala University

Department of Statistics

Zulfazli Zulfazli, Syiah Kuala University

Department of Statistics

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Published

2020-04-28

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Section

Research Articles