Application Of Multiple Linear Regression Method In Predicting Pekanbaru City's Population Growth Rate
DOI:
https://doi.org/10.22303/csrid-.16.2.2024.137-147Keywords:
Multiple Linear Regression, Population Growth, Prediction, Gradient Descent, Pekanbaru CityAbstract
Population growth is a phenomenon with significant implications for the development of a region. Action is needed to anticipate this rapid population growth, one of which is by predicting the population. This study aims to apply Multiple Linear Regression method to predict the population growth rate in Pekanbaru City. The variables of births, male population, and female population are used as predictors in the regression model. Optimization is performed using the Gradient Descent method to improve prediction accuracy. Historical data from 2003 to 2022 is used to train and test the model. The evaluation results show that the optimized multiple linear regression model is able to provide accurate predictions, with a MAPE of 1.09% and RMSE of 0.20618. Further development can be done by considering additional factors and using more advanced optimization methods to improve prediction accuracy. This research is expected to contribute to understanding the factors influencing urban population growth and provide a basis for more effective and sustainable urban development planning.
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