Binary Logistic Regression Analysis of Variables That Influence Poverty Depth Level in West Java Province

Abstract

Poverty continues to be a problem for countries and also regions. The province of West Java is not immune to the problem of poverty, making poverty a matter that must be considered and requires follow-up to alleviate it. This research was conducted with the aim of determining what factors influence poverty depth level in West Java Province and determining the accuracy of the classification obtained from the model. The data used in this research are secondary data in 2022, consisting of data on the poverty depth index, human development index, gini ratio, Gross Regional Domestic Product growth rate, and population growth rate taken from the Central Statistics Agency of West Java. The analysis method used in this research is binary logistic regression based on backward elimination. Factors that influence poverty depth level are the human development index ( ), and gini ratio ( ). The classification accuracy of the model is 81.818%, which means the model is good to use.