Prediction of Life Expectancy Based on Socioeconomic and Health Factors Using Random Forest Regressor Algorithm
Prediksi Angka Harapan Hidup Berdasarkan Faktor Sosioekonomi Dan Kesehatan Menggunakan Algoritma Random Forest Regressor
DOI:
https://doi.org/10.21070/ups.5087Keywords:
Life expectancy prediction, Random Forest Regressor, Correlation analysisAbstract
This research aims to develop a predictive model for life expectancy in various Asian countries using the Random Forest Regressor algorithm. The model is capable of predicting life expectancy with an accuracy rate of 96.5% and a Mean Absolute Error (MAE) of 0.99. Correlation analysis indicates that the "school_year," "HDI," and "BMI" features have a significant impact on life expectancy, highlighting the strong relationship between education, human development, dietary patterns, and societal well-being. The findings of this study can support policy efforts to enhance the welfare and quality of life of populations across different Asian countries, with a focus on education, human development, healthy eating habits, and an active lifestyle.
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