Analysis of Meeting Early Childhood Education Resource Needs Through Monte Carlo Simulation

Accurate resource planning is a critical challenge in managing Early Childhood Education (ECE) institutions, especially in semi-rural areas facing budget constraints and fluctuating student enrollment. This study aims to apply the Monte Carlo Simulation method as a quantitative approach to predict resource needs at PAUD Ceria Mojokerto over one academic year. The research focuses on three main components: teaching staff, stationery supplies, and classroom space. Historical data from the past five years were used to build probability distributions and model student enrollment and attendance rate uncertainties. PAUD Ceria Mojokerto was chosen as a case study due to its representativeness of typical conditions in semi-rural ECE settings. The simulation results indicate that the required number of teaching staff ranges from 2 to 5, stationery supplies range from 103 to 496 units, and classrooms range from 2 to 4 per academic year. These findings highlight that the approach offers more flexible and realistic estimates than conventional deterministic methods. Therefore, ECE administrators are encouraged to integrate quantitative methods such as Monte Carlo Simulation into their operational planning to enhance efficiency, resilience to student population dynamics, and data-driven decision-making. This research contributes to developing data-driven educational planning practices, particularly in resource-limited settings.