The Role of Exponential Growth Model in Predicting Population Growth: A Study of Demographic Data in NTB Province

Abstract

Abstracts: This study aims to apply an exponential growth model in predicting the population of West Nusa Tenggara (NTB) Province based on annual demographic data from 2014 to 2024. By using Winter's exponential smoothing method that includes level, trend, and seasonal components, this model is able to capture population growth patterns that tend to increase consistently from year to year. The calculation results show that the population of NTB is predicted to continue to grow until it reaches 7,253,193 people in 2034. The exponential model is proven to have good accuracy in following historical patterns, as shown by the conformity between the projected graph and the actual data. The advantages of this method lie in the simplicity of the process, the speed of adaptation to the latest data, and its efficiency in producing short-term estimates. The results of this study are expected to be used as a basis for designing more targeted development policies, especially in the education, health, and infrastructure sectors. To improve the accuracy and coverage of the model in the future, it is recommended that future research include additional variables such as migration, birth and death rates, and socioeconomic conditions, as well as compare the exponential model with other forecasting methods such as ARIMA or machine learning approaches. In addition, the integration of prediction results into a geographic information system (GIS) could be a strategic step to support a more interactive and informative presentation of data for policy makers.