Comparative Analysis of Exponential and Logistic Models on Population Growth (Case Study: Ogan Komering Ulu Regency) - Suryani, Putri; Sutrisno, Agus; Zakaria, La (EduMatSains : Jurnal Pendidikan, Matematika dan Sains, 2026)
Population growth is an important indicator in regional development planning as it relates to resource needs, public services, and the formulation of social and economic policies. This study aims to analyze and compare the performance of the exponential model and the logistic model in projecting the population growth of Ogan Komering Ulu (OKU) Regency for the 2014–2025 period, as well as determining the best model based on the Mean Absolute Percentage Error (MAPE) value. This research uses a quantitative approach with a comparative descriptive method, utilizing secondary data obtained from the Central Bureau of Statistics (BPS). Model parameter estimation was carried out using the Generalized Reduced Gradient (GRG) method through the Solver feature in Microsoft Excel with the objective function of minimizing the MAPE value. The results of the analysis show that both models have a very high level of accuracy. The exponential model produces a MAPE value of 0.4% with = 0.01, while the logistic model produces a MAPE value of 0.3% with = 0.038 and = 500,000 people. Based on these values, the logistic model has a smaller error rate and is thus considered superior in representing the actual data. Accordingly, the logistic model is established as the best model in this study with the equation , which can be used as a basis for population growth projections in Ogan Komering Ulu Regency, particularly for long-term analysis.