BibTex Citation Data :
@article{J.Gauss14704, author = {Mas'ad Mas'ad and Hasbi Yasin and Di Maruddani}, title = {ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PERSENTASE PENDUDUK MISKIN DI JAWA TENGAH DENGAN METODE GEOGRAPHICALLY WEIGHTED PRINCIPAL COMPONENTS ANALYSIS (GWPCA) ADAPTIVE BANDWIDTH}, journal = {Jurnal Gaussian}, volume = {5}, number = {3}, year = {2016}, keywords = {poverty, multivariate, correlation, spatial effect, GWPCA adaptive bandwidth.}, abstract = { Poverty is one of the fundamental problems that is faced by developing country such as Indonesia. One of provinces with high poverty in Java is Central Java. The factors affecting poverty in the districts/cities in Central Java are Human Development Index, pre-prosperous family, population density, Labor Force Participation Rate, and Regional Minimum Wage. Variables which is affecting poverty percentage are multivariate data that have spatial effect and are correlated to each other. Therefore, Geographically Weighted Principal Components Analysis (GWPCA) Adaptive Bandwidth is suitable to analyze what dominant factor that effects poverty percentage in the districts/cities in Central Java. GWPCA Adaptive Bandwidth is a multivariate analysis method that is used to remove the correlation in multivariate data that have spatial effects with the distance weighting measure and the extent of location influence relative to each other location conforming to the variance size of data density. The result of this research the variables affecting poverty percentage each region can be replaced by new variables called principal components which can explain 82% of the original variables. This research also found five regional groups that have different poverty-percentage-affecting characterics. Keywords : poverty, multivariate, correlation, spatial effect, GWPCA adaptive bandwidth. }, issn = {2339-2541}, pages = {487--496} doi = {10.14710/j.gauss.5.3.487-496}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/14704} }
Refworks Citation Data :
Poverty is one of the fundamental problems that is faced by developing country such as Indonesia. One of provinces with high poverty in Java is Central Java. The factors affecting poverty in the districts/cities in Central Java are Human Development Index, pre-prosperous family, population density, Labor Force Participation Rate, and Regional Minimum Wage. Variables which is affecting poverty percentage are multivariate data that have spatial effect and are correlated to each other. Therefore, Geographically Weighted Principal Components Analysis (GWPCA) Adaptive Bandwidth is suitable to analyze what dominant factor that effects poverty percentage in the districts/cities in Central Java. GWPCA Adaptive Bandwidth is a multivariate analysis method that is used to remove the correlation in multivariate data that have spatial effects with the distance weighting measure and the extent of location influence relative to each other location conforming to the variance size of data density. The result of this research the variables affecting poverty percentage each region can be replaced by new variables called principal components which can explain 82% of the original variables. This research also found five regional groups that have different poverty-percentage-affecting characterics.
Keywords : poverty, multivariate, correlation, spatial effect, GWPCA adaptive bandwidth.
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