Numerical Modeling of Population Growth in Kedah

Abstract

Population growth modeling requires mathematical methods to simulate data for more effective planning and decision-making related to issues such as socioeconomic development, environmental sustainability, resource allocation, manpower, and more. In line with these concerns, a state like Kedah also needs well-aligned development plans that reflect its population trends. Due to the high cost of conducting census exercises, this study employs various mathematical models namely polynomial regression, exponential model, and Runge-Kutta fourth order (RK4) method to estimate and predict the future population growth of Kedah. The three models are compared with one another and validated against actual population data and projections from the Department of Statistics Malaysia (DOSM) for the period 1970 to 2060. The best-performing model is identified based on its R-squared value, where a value approaching 1 indicates high accuracy and model significance. The results conclude that the RK4 method is the most accurate with an R-squared value of 0.99921329.