Application of the Logistic Growth Model for Forecasting Population Dynamics in Makassar - Pratama, Muhammad Isbar; Ja'faruddin, Ja'faruddin; Ansi, Ansi (Journal of Mathematics, Computations and Statistics, 2026)
The continuous increase in population requires accurate forecasting methods to support development planning. This study aims to apply the logistic model to forecast the population of Makassar City using data from the Central Bureau of Statistics (BPS) for the period 2015–2024. The research employed a quantitative descriptive method with logistic differential equation modeling. The carrying capacity (K) parameter was determined analytically, while the growth rate (r) was calculated annually, resulting in nine different logistic models. The accuracy of each model was evaluated using the Mean Absolute Percentage Error (MAPE) to identify the best model. The results indicate that the ninth logistic model produced the smallest MAPE value of 1,95% and was used to project the population for 2030–2035. Based on this model, the population of Makassar City is projected to reach 1,495,521 people in 2030 and increase to 1,510,058 people in 2035. These findings demonstrate that the logistic model can serve as an effective tool for population growth forecasting to support sustainable development planning.