Management Analysis on Queuing System in Terminal Bus Using Multichannel Model

Zahran M. Halim and Suliadi F. Sufahani
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Zahran M. Halim: Department of Mathematics and Science, Faculty of Applied Science and Technology, University Tun Hussein Onn Malaysia, Pagoh Campus, 84600 Pagoh, Johor, Malaysia
Suliadi F. Sufahani: Department of Mathematics and Science, Faculty of Applied Science and Technology, University Tun Hussein Onn Malaysia, Pagoh Campus, 84600 Pagoh, Johor, Malaysia

International Journal of Research and Innovation in Social Science, 2025, vol. 9, issue 3, 5061-5071

Abstract: Queuing system is a common behavior of people that arrive in a facility to wait for certain services that are being offered by the service facility to make our life easier. There has been three problem that were outlined in the research. First is failure in management. Second, awareness of the application that were built by the terminal bus. Last but not least, lack of networking between different gate terminals. Hence, three objectives were discussed in the study such as analysing the SIT and Duta Bus Station datasets by using a multichannel queuing model, evaluating daily queuing system cost for SIT and Duta Bus Station by referring to queuing theory, and measuring the performance of either average service rate is greater than the average arrival rate in both terminals mentioned earlier. In this research, we used only one method which is the multichannel queuing model M/M/C by selecting only 10 counters for both terminals as a channel, m. The datasets were collected by contacting higher officers in both terminals. From the result we can say that SIT has a greater average arrival rate and average service rate compared to Duta Bus Station meanwhile Duta Bus Station has a greater total daily service cost and waiting cost compared to SIT. Finally, what we can conclude from the research is we know for sure that both terminals need improvements in the facility and act of service so that they will gain more customers and the service effectively reducing the queuing time

Date: 2025
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