Article Per Year (5 Year)
p-Index From 2019 - 2024
0
P-Index
This Author published in this journals
All Journal Jurnal Gaussian
Firda Shintia Dewi
Unknown Affiliation
Other

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
PEMODELAN STATUS KESEJAHTERAAN DAERAH KABUPATEN ATAU KOTA DI JAWA TENGAH MENGGUNAKAN GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION SEMIPARAMETRIC Firda Shintia Dewi; Hasbi Yasin; Sugito Sugito
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (540.568 KB) | DOI: 10.14710/j.gauss.v4i1.8102

Abstract

Welfare in society is one of the most important aspects in ensuring the realization of the social where people have a good level of welfare. Benchmarks achieved prosperity is the fulfillment of basic needs of society as feasible. Statistical methods have been developed for the analysis of spatial data by taking into account factors that Geographically Weighted Logistic Regression Semiparametric (GWLRS). GWLRS is a local form of the logistic regression where there are parameters that are influenced by the location (Geographically varying coefficient) and the parameters that are not influenced by the location (fixed coefficient). Selection of the optimum bandwidth using Cross Validation (CV). Model GWLRS Welfare Status district or city in Central Java showed that GWLRS models differ significantly from the logistic regression model. And models generated for each area will be different from each other. To get the best models, the number of models to be evaluated. One method for selecting the best model is the value of the Akaike Information Criterion (AIC). Based on AIC obtained the best model is the model GWLRS because it has the smallest AIC value of 46.11213 with a classification accuracy of 77.14%. Keywords: Welfare, Geographically Weighted Logistic Regression Semiparametric, Cross Validation, Akaike Information Criterion
Co-Authors Hasbi Yasin Sugito Sugito