SYSTEMATIC LITERATURE REVIEW (SLR) : PENGELOLAAN ANTRIAN DALAM SISTEM PELAYANAN
Abstract
Queues are a problem that often arises in the service system due to an imbalance between the level of service demand and the available service capacity. A queue that is not well managed can lead to increased waiting times, decreased service quality, and reduced service user satisfaction. This research uses the Systematic Literature Review (SLR) approach with the aim of identifying the concept of queue management, the factors that affect its effectiveness, as well as the influence of queuing management on the quality of service and service user satisfaction. Data was obtained from the Scopus database in the publication of 2025 with the keywords “queue” and “service”. From the initial search results as many as 90 documents, after going through the inclusion and exclusion process the criteria obtained 20 more analyzed articles. The results showed that the management of queues is generally based on the theory of queues through the application of single-server and multi-server models, optimization of service capacity, as well as the use of queuing performance indicators. The effectiveness of the management of the queue is influenced by the rate of arrival and service, the number of service facilities, priority policies, variability of service time, and the utilization of technology and optimization methods. In addition, effective management of queues is proven to have a positive effect on the decline of waiting times, improving the quality of service, and satisfaction of service users.
References
García-cáceres, R. G., Prado-téllez, A. G., & Escobar-velásquez, J. W. (2025). Sustainable Integral Optimization of Service Queues : A Human-Centered Approach Using IAM and SMAA. 1–25.
Latifah, L., & Ritonga, I. (2020). Systematic Literature Review (SLR): Kompetensi Sumber Daya Insani Bagi Perkembangan Perbankan Syariah Di Indonesia. Al Maal: Journal of Islamic Economics and Banking, 2(1), 63. https://doi.org/10.31000/almaal.v2i1.2763
Mitzenmacher, M., Shahout, R., & Mitzenmacher, M. (2025). Queueing , Predictions , and Large Language Models : Challenges and Open Problems Queueing , Predictions , and Large Language Models : December. https://doi.org/10.1287/stsy.2025.0106
Sakuma, Y., & Aung, Y. L. (2025). Results in Applied Mathematics A numerically stable formula for the conditional distribution of the residual service time in the ? ? ∕ ? ? ∕ 1 queue. Results in Applied Mathematics, 27, 100603. https://doi.org/10.1016/j.rinam.2025.100603
Težak, S., & Sever, D. (2025). Optimization of Operations in Bus Company Service Workshops Using Queueing Theory.
Wang, C., Tian, R., Hu, K., Chen, Y., & Ku, T. (2025). OPEN A Markov decision optimization of medical service resources for two- class patient queues in emergency departments via particle swarm optimization algorithm. 1–29.
Yang, K., Xu, C., Qiao, G., Zhong, J., & Zhang, X. (2025). Intelligent Queue Scheduling Method for SPMA-Based UAV Networks. 1–20.
