Binjai Train Ticket Counter Queue Simulation Using Weibull Service Distribution
Keywords:simulazion, ticket, train, weibull distribution, servicing efficiency, binjai station.
This research aims to improve the efficiency of train ticket counter services at Binjai Station through the use of Weibull service distribution-based queuing simulations. Long queues and excessive waiting times are often problems at many train stations, and this research aims to address these problems.This study collects queuing data from train ticket booths at Binjai Station over a certain period and analyzes them to identify existing queuing patterns. The Weibull service distribution was chosen as the appropriate model to describe the ticket counter service time, because this distribution has the flexibility to handle variations in service time well.
Queue simulation is carried out using simulation software that models the queuing process at the train ticket counter. Weibull distribution parameters are integrated into the simulation to predict service time at the ticket counter. In this simulation, various scenarios and strategies for improving service efficiency are evaluated to identify the best alternative that can be implemented at Binjai Station. The results of this study will provide guidance to the management of the Binjai train station in making decisions regarding increasing the efficiency of ticket counter services. By optimizing service time and reducing customer waiting time, it is expected to increase customer satisfaction and operational efficiency of train stations.
A. M. H. Pardede and R. Novriyenni Hartono, “Menggunakan Metode Hyperexponential,” vol. 3, no. 4, pp. 33–43, 2018.
Chairijal, Novriyenni, and Nurhayati, “Simulasi Antrian Pelayanan Pendaftaran Pasien Di Uptd Puskesmas Tanah Tinggi Dengan Metode Eksponensial,” J. Tek. Inform. Kaputama, vol. 6, no. 1, pp. 275–283, 2022.
S. A. Thamrin, Azhar, and A. K. Jaya, “Penaksiran Parameter Distribusi Weibull dengan Metode Bayesian survival dan Maksimum Likelihood,” Keteknikan dan Sains – LPPM UNHAS, vol. 1, no. 2, pp. 74–79, 2018.
J. Gaussian, “1 , 2 , 3 1,” vol. 3, pp. 761–770, 2014.
Y. Prihati, “Simulasi Dan Permodelan Sistem Antrian Pelanggan di Loket Pembayaran Rekening XYZ Semarang,” Maj. Ilm. Inform., vol. 3, no. 3, pp. 1–20, 2012.
L. G. Otaya, “Distribusi Probabilitas Weibull Dan Aplikasinya,” J. Manaj. Pendidik. Islam, vol. 4, no. 2, pp. 44–66, 2016.
Y. G. Nengsih, “Sistem Antrian Rekam Medis Pasien Di Rumah Sakit Menggunakan Model Multi Channel Dengan Pola Poisson,” vol. 5, no. 2, pp. 121–131, 2020.
D. Rahayu and H. Fahmi, “Simulasi Antrian Pembuatan Sim Di Sat Lantas Polres Deli Serdang Menggunakan Metode Eksponensial,” vol. 3, no. 3, pp. 23–28, 2021.
How to Cite
Copyright (c) 2023 Journal of Artificial Intelligence and Engineering Applications (JAIEA)
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.