When analyzing real systems, collecting field data can be difficult. Therefore, many methods have been developed to generate artificial random numbers. One of the fundamental methods is the Linear Congruential Generation (LCG) method. It can generate random numbers based on the values of its parameters. The aim of this paper is to identify the key parameter that has the highest impact on the performance of the LCG method, particularly in terms of the random number repetition period. To do this, the Design of Experiment (DOE) technique was used, and a model was developed using Minitab software. The experiment was conducted five times, and the average was taken for better results. The Python code of the LCG method was used to determine the random number repetition period. According to the results of the study, it was found that the parameter "m" had the highest impact on the performance of the LCG method, followed by "a", "c", and "Seed" respectively.