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Esther Nababan
Faculty of Mathematic and Natural Science
Computer Science & IT

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Randomness of Poisson Distributed Random Number in the Queue System Ernestasia; Esther Nababan; Asima Manurung
Data Science: Journal of Computing and Applied Informatics Vol. 3 No. 2 (2019): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (626.521 KB) | DOI: 10.32734/jocai.v3.i2-1128

Abstract

In the queuing system, inter arrival variable and service time variable are probabilistic and its pattern follow a Poisson distribution. Simulations experiment for performance measurement of a queuing system required random data. In practice, random data is built using an application program. Pseudorandom data generated from application programs often have different patterns of randomness, although in each experiment simulated the same data distribution. Level of randomness may cause the results of simulation experiments experienced statistically significant deviations, especially on problems with stochastic variables. Statistical deviation can cause errors in interpreting the results of simulation experiments, especially in the assessment of the performance of the queuing system. It is required to evaluate whether the level of randomness of pseudorandom data effect on simulation results of performance measurement of a system. Simulation experiments on a simple queuing system (M / M / 1) was carried out by using a pseudorandom number generator. Application program used to generate pseudorandom numbers is Fortran90. The experimental results show that the greater the amount of pseudorandom data, the greater the statistical deviations occur, and the smaller the degree of randomness of data. This affects the results of the simulation system in which there is a probabilistic variable that require random data to conduct simulation
Co-Authors Asima Manurung Ernestasia