Eksponensial
Vol. 11 No. 1 (2020)

Penerapan Model Geographically Weighted Logistic Regression Pada Data Status Kesejahteraan Masyarakat di Kalimantan Tahun 2017

Pratiwi, Nadya (Unknown)
Suyitno, Suyitno (Unknown)
Siringoringo, Meiliyani (Unknown)



Article Info

Publish Date
19 Jan 2021

Abstract

Geographically Weighted Logistic Regression (GWLR) model is a regression model developed from logistic regression which is applied to spatial data. The aims of research is a GWLR model determination on dichotomous data of community welfare status based on the Human Development Index (HDI) and to find the factors influencing the probability of high welfare status of each Regency/City on Kalimantan Island in 2017. Parameters estimation of the GWLR model was done at each observation location using a weighted Maximum Likelihood Estimation (MLE) method and maximum likelihood estimator was obtained by Newton Raphson iterative method. Spatial weighting on parameter estimation was determined using Adaptive Gaussian weighting function and optimum bandwidth was determined using Generalized Cross-Validation (GCV) criterion. Based on the result of GWLR parameter testing, it was concluded that the factors influencing the probability of high welfare status of Regency/City on Kalimantan Island in 2017 were school enrollment rates (senior high school), the number of health workers, real per capita income and the open unemployment rate.

Copyrights © 2020






Journal Info

Abbrev

exponensial

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other

Description

Jurnal Eksponensial is a scientific journal that publishes articles of statistics and its application. This journal This journal is intended for researchers and readers who are interested of statistics and its ...