Comparative analysis of exponential and logistic growth models for predicting motorized vehicle population in Indonesia

Abstrak

The increasing mobility of the Indonesian population has led to a high demand for motorized vehicles, posing significant challenges for infrastructure management and environmental sustainability. This study aims to compare the accuracy of exponential and logistic growth models and to predict the motorized vehicle population in Indonesia. Motorized vehicle data for the period 2015–2022 from the Central Bureau of Statistics (BPS) were processed using MS Excel to determine the parameters for both models and subsequently simulated using MATLAB. The optimal model was selected based on graphical plot results and the lowest Mean Absolute Percentage Error (MAPE) value. The analysis results indicate that the logistic model provides higher accuracy (MAPE = 0.54%) compared to the exponential model (MAPE = 1.50%). The motorized vehicle population is projected to reach 152,520,752 units in 2023 and is expected to continue increasing to 174,657,192 units by 2030. Furthermore, the logistic model demonstrates that the population growth rate will decelerate as it approaches its carrying capacity (K = 189,659,261 units). These findings serve as critical considerations for the government in formulating infrastructure planning and environmental protection strategies against emissions from operating motorized vehicles.