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All Journal International Journal of Computing Science and Applied Mathematics-IJCSAM
Bryan Given Christiano Ginzel
Universitas Airlangga
Mathematics

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Analyzing the Influence of Gross Domestic Product on the Human Development Index Worldwide in 2021 Using a Nonparametric Regression Approach Based on Penalized Spline Estimator Dita Amelia; Azizah Atsariyyah Zhafira; Bryan Given Christiano Ginzel; Fery Yulian Putra; Yoga Setya Wibawa
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 11 No. 2 (2025)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v11i2.8851

Abstract

People’s welfare is a universal goal that is the main focus of all countries in the world. One of the indicators used to measure welfare is the Human Development Index (HDI), which includes education, health and per capita income. On the other hand, Gross Domestic Product (GDP) is the main measure of a region’s economic growth. This research aims to highlight how regional economic dynamics affect human welfare in the world in 2021 and the data source was obtained from OurWorldInData. This research uses nonparametric regression with a penalized spline estimator approach. Penalized Spline analysis shows that the best model for predicting HDI based on GDP per capita is to use 2 knot points, namely k1=8000 and k2=50000. This model produces a Mean Squared Error (MSE) value of 0.0018 and Generalized Cross Validation (GCV) of 0.0019. In addition, this model has the ability to explain response variability of R2=91.58%. The grouping of countries by GDP per capita reveals that economic improvement impacts human development differently across income levels. By tailoring strategies to specific income groups, policymakers can more effectively enhance human development outcomes, fostering a more equitable and prosperous society
Co-Authors Azizah Atsariyyah Zhafira Dita Amelia Fery Yulian Putra Yoga Setya Wibawa