Nurhasanah, Nunung and Widiarti, Widiarti and Nurvazly, Dina Eka and Usman, Mustofa (2024) Penerapan Model Geographically Weighted Logistic Regression dengan Fungsi Pembobot Adaptive Gaussian Kernel pada Data Kemiskinan. Jambura Journal of Mathematics, 6 (2). pp. 204-211. ISSN 2656-1344

Text Nunung dkk_JAMBURA 2024.pdf Download (1MB)

Abstract

Regression analysis is one statistical method used to determine the relationship between a dependent variable and one or more independent variables. Dependent variables that are categorical are analyzed using logistic regression analysis. Geographically Weighted Logistic Regression (GWLR) is a method that is a local version of logistic regression, where location factors are considered. This method assumes that the dependent variable data are distributed binomially. In this study, the GWLR method is used to determine the factors influencing the poverty percentage in West Java Province in 2022 using an adaptive Gaussian kernel weighting function. The variables used are per capita expenditure, average length of schooling, Gross Regional Domestic Product (GRDP) per capita, and population density. The results of this study indicate that the variables of per capita expenditure, Gross Regional Domestic Product (GRDP) per capita, and population density significantly influence the poverty percentage in West Java Province in 2022.

Item Type:	Article
Subjects:	Q Science > QA Mathematics
Divisions:	Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Prodi Matematika
Depositing User:	WIDIARTI
Date Deposited:	06 Aug 2024 07:59
Last Modified:	06 Aug 2024 07:59
URI:	http://repository.lppm.unila.ac.id/id/eprint/54032

Actions (login required)

View Item