Simulasi Metode Monte Carlo untuk Mengatur Sistem Antrian Truk
DOI:
https://doi.org/10.35134/komtekinfo.v11i3.552Keywords:
Technology Information, Simulation, Prediction, Queue, Monte CarloAbstract
This research focuses on optimizing pozzolan truck queue management at PT. Danas Putra Mandiri through the application of the Monte Carlo method. The main objective of this research is to develop and implement a simulation application that is able to predict and calculate the average availability of trucks in a certain time unit, with the ultimate goal of increasing the company's operational efficiency. In industries that rely on the transportation of raw materials such as pozzolan, effective truck queue management is key to avoiding distribution delays and reducing operational costs. A queue is a service from one or more services that is caused by the need for services exceeding the capacity of the service or service facilities, so that customers who arrive cannot immediately receive service due to busyness in the service. The method used in this research is the Monte Carlo method. Monte Carlo is an experiment of various elements of probability using random samples. The Monte Carlo method is useful for solving quantitative problems with real or physical processing. This method has the ability to simulate and manage queues that occur in companies. PT Danas Putra Mandiri is one of the companies operating in the mining sector which supplies pozzolan to PT Semen Padang. The pozzolan delivery process uses trucks. The delivery process using trucks can affect the availability of the number of trucks in the company. The data used in this research is data from January 2023 - December 2023 with a total of 1619 data. Data taken through the admin of PT. DANAS PUTRA MANDIRI. Based on simulation predictions of queues on trucks, results were obtained with an average accuracy of 80.6%. The queuing simulation results show that the application of the Monte Carlo method can effectively reduce truck waiting times and increase the availability of trucks for rental, which ultimately contributes to increasing the company's operational efficiency.
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