<![CDATA[Population growth is a vital aspect of regional planning; however, the limited availability of census data over certain periods poses challenges for strategic decision-making. Therefore, a predictive method capable of accurately filling data gaps is essential. This study employs the Lagrange polynomial interpolation method, implemented in MATLAB, to model and predict the population of Sleman Regency from 2016 to 2045, including estimates for years beyond the available data. The analysis results indicate that the Lagrange interpolation method can generate reasonably accurate predictions and reflect a stable growth trend following the COVID-19 pandemic. The use of MATLAB facilitates calculations and visualization, thereby enhancing the effectiveness of the analysis. These findings affirm that Lagrange interpolation is an effective tool for demographic data prediction, which is crucial for supporting data-driven policymaking toward sustainable development. Based on these results, it is expected that the accuracy of regional and national development strategies can be improved in addressing future socio-economic dynamics.]]>
Copyrights © 2025
