Penerapan Model Antrean Multi Channel Multi Phase Pada Sistem Pelayanan Warunge Bapak Coffee

Authors

  • Muhammad Bahril Ihza Universitas Islam Nahdlatul Ulama Jepara
  • Dwi Retna Sulistyawati Universitas Islam Nahdlatul Ulama Jepara
  • Gunawan Mohammad Universitas Islam Nahdlatul Ulama Jepara
  • Muhammad Choiru Zulfa Universitas Islam Nahdlatul Ulama Jepara
  • Budi Lofian Universitas Islam Nahdlatul Ulama Jepara

DOI:

https://doi.org/10.61722/jinu.v2i2.3737

Keywords:

Multi Channel Multi Phase; Optimization; POM-QM V5; Queuing System

Abstract

Coffee shops are one of the leading coffee places nowadays which are often visited by young people and adults. Shop owners usually often ignore the long cashier queues. This also happened at Warunge Bapak Coffee, where on weekends the cashier section had quite a long queue. Improvements are continuously made to produce good service. However, the length of time you wait in line will affect the quality of the service provided. This research focuses on services in the cashier section with the aim of reducing long queues at cashier services, Based on observation data and data processing using the Multi Channel Multi Phase queuing method with POM-QM V5 for Windows software, because during observations in this section there is the potential for waiting times. The results show that the average length of waiting time is very dependent on the level of service speed. There are 11 customers every hour. Where the percentage of utilization optimization with these 2 servers is 30.6%. This queuing system can be said to be optimal because the average level of service is greater than the level of customer arrival. However, in actual practice the number of customers who come to Warunge Bapak Coffee is almost the same as the level of service. Thus, it is recommended that the coffee shop improve its performance so that customers who come feel more satisfied, and it can be concluded that there needs to be improvements to the server section at the cashier by adding workers on a part time system to anticipate a surge in customers coming to reduce waiting time.

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Published

2025-01-06