Machine Learning Approach to Analyze the Relationship Between State Defense Index and Human Development to Strengthen National Defense

Abstract

In efforts to strengthen national defense, it is important to understand how factors in human development, such as education, health, and economic welfare, can influence public awareness of national defense. This study aims to analyze the relationship between the National Defense Index (IBN) and the Human Development Index (IPM) in Indonesia using a Machine learning approach. To strengthen national defense, it is essential to understand how factors in human development, such as education, health, and economic welfare, can affect public awareness of national defense. Machine learning methods are applied to analyze the significant relationship between IBN and IPM, which is expected to provide insights for the development of more data-driven national defense policies. The results show that the Machine learning model can predict IBN values with high accuracy, supported by a Mean Squared Error (MSE) of 0.000638 and an R-squared value of 0.9026. This indicates that 90.26% of the variability in IBN values can be explained by the model, suggesting accurate predictions that are relevant for data-driven policies. Collaboration with various stakeholders is expected to enhance the application of these findings in further studies and the formulation of national defense policies.