Application of Principal Component Regression in Analyzing Factors Affecting Human Development Index

  • Susilawati S
  • Didiharyono D
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Abstract

The human development index is an indicator to measure the quality of people's lives. If the human development index number increases, the better the quality of people's lives. There are many factors or variables that affect the level of the human development index, ranging from economic issues, education, health and other factors. However, not all factors have a positive and significant effect. Thus, this study aims to determine the factors that significantly affect the human development index in South Sulawesi. The method used in this study is principal component regression which involves many variables. The variables involved are expected length of schooling, average length of schooling, percentage of population with the highest Diploma, Bachelor and Masters education, school enrollment rate for people aged 7-24 years, percentage of poor people, spending per capita, and life expectancy. From the results of data processing using principal component analysis, 4 main components are obtained which represent the other components, for principal component regression, taking into account the cumulative proportion of > 80%. The results of this study indicate that the human development index in South Sulawesi is influenced by all the variables involved, which is equal to 95.7%. With the variable percentage of poverty being one of the variables that has a negative effect on HDI in South Sulawesi which shows that the higher the percentage of poverty, the lower the human development index. Thus, in order to increase the human development index in Indonesia, it is necessary to take strategic steps to improve people's welfare.

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Susilawati, S., & Didiharyono, D. (2023). Application of Principal Component Regression in Analyzing Factors Affecting Human Development Index. Jurnal Varian, 6(2), 199–208. https://doi.org/10.30812/varian.v6i2.2366

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