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Djoni Hatidja
Department of Mathematics, Faculty of Mathematics and Natural Sciences, Sam Ratulangi University, Manado, Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Mathematics Physics

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Kernel Performance in Geographically Weighted Regression Model to Determine Factors Affecting Human Development Index in South Sulawesi Province Angelia Fransisca Adatunaung; Djoni Hatidja; Winsy Christo Deilan Weku
Jurnal Ilmiah Sains Volume 23 Nomor 2, Oktober 2023
Publisher : Sam Ratulangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35799/jis.v23i2.48867

Abstract

The aims of this study was determine at kernel performance by selecting the best model from three different types of kernels and determining the factors that influence the Human Development Index in South Sulawesi Province using the Geographically Weighted Regression (GWR) model This study uses secondary data from the Central Bureau of Statistics of South Sulawesi Province with independent variables namely human development index (HDI, Y) and the dependent variable namely life expectancy (UHH) (X1), per capita expenditures (X2) and gross regional domestic product (GRDP) (X3) and the longitude and latitude values ​​obtained from the google maps application. The methods carried out in this study are the GWR method and the kernels used are gaussian kernels, bisquare kernels and tricube kernels. The results of this study show that the best model that can be used is the GWR model with a tricube kernel with AIC values ​​= 81.5543700 and R2 = 90.67 percent. GWR Model with kernel tricube is able to determine the factors that influence the human development index in South Sulawesi in 2022. Keywords: Geographically Weighted Regression; human development index; tricube kernel
Application of Nonparametric Spline Regression and Fourier Series to Model Gross Regional Domestic Product in Indonesia Marklif Esriy Mocodompis; Deiby Tineke Salaki; Djoni Hatidja
Jurnal Ilmiah Sains Volume 23 Nomor 2, Oktober 2023
Publisher : Sam Ratulangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35799/jis.v23i2.48868

Abstract

The purpose of this study was to model the Gross Regional Domestic Product (GRDP) in Indonesia using nonparametric spline regression and Fourier series. The data used includes the GRDP of 34 provinces in Indonesia, with predictor variables such as labor force participation rate, foreign direct investment, local revenue, minimum provincial wage, and human development index. In the nonparametric spline regression, the determination of the optimal knot points is performed with one to three knots, and the optimal knot points are obtained by minimizing the Generalized Cross Validation (GCV) value, resulting in three optimal knot points. In the nonparametric Fourier series regression, calculations are performed for one to three oscillation points, and the optimal oscillation points are obtained based on the minimum GCV value, resulting in three optimal oscillation points. Therefore, the best nonparametric spline regression model utilizes three knot points, while the Fourier series model utilizes three oscillation points for modeling the GRDP in Indonesia. Keywords: Fourier Series; nonparametric regression; oscillation point; spline
Co-Authors Angelia Fransisca Adatunaung Deiby Tineke Salaki Marklif Esriy Mocodompis Winsy Christo Deilan Weku