Abstract

The aim of this research is to 1) determine the influence of life expectancy on the human development index in districts/cities in Bali Province; 2) Knowing the effect of average length of schooling on the human development index in districts/cities in Bali Province; 3) Knowing the effect of poverty levels on the human development index in districts/cities in Bali Province; 4) Knowing the effect of life expectancy, average length of schooling, and poverty level on the human development index in districts/cities in Bali Province. Research was conducted in districts/cities in Bali Province. This research was conducted in districts/cities in Bali Province using 117 observation points taking into consideration the occurrence of disparities in life expectancy, average length of schooling, poverty level, and human development index between districts/cities in Bali Province. This research uses data released by the Bali Province Central Statistics Agency (BPS). The object of this research focuses on four main variables, namely life expectancy, average years of schooling, poverty level, and human development index. The data analysis techniques used to solve the problems in this research are: Classic Assumption Test and Hypothesis Testing with Multiple Linear Regression Analysis Techniques.Based on the results of the analysis, it is known that with a confidence level of 98.1 percent, all independent variables have a significant effect, both simultaneously and partially, on the dependent variable. This means that the factors studied which consist of life expectancy, average length of schooling and poverty level influence the human development index in districts/cities in Bali Province have a significant effect both partially and simultaneously. If we look at the high coefficient of determination, 98.1 percent of the variation in life expectancy, average years of schooling and poverty levels, which can explain variations in the human development index in districts/cities in Bali Province, so that they can provide different contributions for each model. Studies.

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