Prediksi Jumlah Mahasiswa Baru Program Studi Teknik Industri Universitas Al-Azhar Medan Menggunakan Simulasi Monte Carlo
DOI:
https://doi.org/10.31004/jutin.v9i1.55923Keywords:
Monte Carlo, Enrollment Prediction, Industrial Engineering, Stochastic Simulation, Random Number GenerationAbstract
This study aims to forecast the number of incoming students in the Industrial Engineering Program at Al-Azhar University Medan using Monte Carlo simulation as a probability-based approach. Historical enrollment data from 2023–2025 were utilized to construct an empirical probability distribution, totaling 180 students. The research procedure includes probability calculation, cumulative probability determination, establishment of random number intervals on a 01–100 scale, and generation of pseudo-random numbers using the Mixed Congruential Random Number Generator (MCRNG) with parameters satisfying the Hull-Dobell theorem. A total of 1,000 simulation iterations were performed to obtain a stable output distribution. The results indicate that simulated probabilities closely approximate theoretical values: 15.00% (2023), 35.00% (2024), and 50.00% (2025), with an average absolute deviation of 0.0037. Based on the probabilistic pattern and historical growth trend, the projected enrollment for 2026 is estimated at 90–95 students. These findings demonstrate that Monte Carlo simulation is an effective tool for data-driven academic planning.References
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Copyright (c) 2026 Bani Septiawan, Misnaini Misnaini, Muhammad Ikhwan, Lindi Cistia Praba, Ilham Basith Abdillah, Muhammad Dzikri Ramadhan
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