Modify Linear Congruent Generator Algorithms Using Inverse Elements of Modulo Multiplication for Randomizing Exams - Sujono; Maxrizal; Irawadi, Syafrul; Prayanti, Baiq Desy Aniska (2022 4th International Conference on Cybernetics and Intelligent System (ICORIS), 2022)
Linear Congruent Generator randomization results are pretty easy to predict. In addition, improper parameter selection in LGC will make the LCG period predictable, and randomization results will repeat quickly. To overcome the weakness of LCG, researchers have developed LCG and hybrid variants, such as CLCG, dual CLCD, RSA hybrid, Hybrid ECC and Fibonacci hybrid. Although LCG variants and combinations produce better random results, the computational level is more complex than LCG. In this study, we propose a modification of LCG by adding an inverse element to the multiplication mod m. Like CLCG, this research is an LCG which is continued by calculating the inverse element of the multiplication mod m. The results showed that the resulting modified LCG worked well, and the randomization effect was more random than the original LCG.