TY - GEN
T1 - Analysis of variables affecting unemployment rate and detecting for cluster in West Java, Central Java, and East Java in 2012
AU - Samuel, Putra A.
AU - Widyaningsih, Yekti
AU - Lestari, Dian
N1 - Publisher Copyright:
© 2016 AIP Publishing LLC.
PY - 2016/2/11
Y1 - 2016/2/11
N2 - The objective of this study is modeling the Unemployment Rate (UR) in West Java, Central Java, and East Java, with rate of disease, infant mortality rate, educational level, population size, proportion of married people, and GDRP as the explanatory variables. Spatial factors are also considered in the modeling since the closer the distance, the higher the correlation. This study uses the secondary data from BPS (Badan Pusat Statistik). The data will be analyzed using Moran I test, to obtain the information about spatial dependence, and using Spatial Autoregressive modeling to obtain the information, which variables are significant affecting UR and how great the influence of the spatial factors. The result is, variables proportion of married people, rate of disease, and population size are related significantly to UR. In all three regions, the Hotspot of unemployed will also be detected districts/cities using Spatial Scan Statistics Method. The results are 22 districts/cities as a regional group with the highest unemployed (Most likely cluster) in the study area; 2 districts/cities as a regional group with the highest unemployed in West Java; 1 district/city as a regional groups with the highest unemployed in Central Java; 15 districts/cities as a regional group with the highest unemployed in East Java.
AB - The objective of this study is modeling the Unemployment Rate (UR) in West Java, Central Java, and East Java, with rate of disease, infant mortality rate, educational level, population size, proportion of married people, and GDRP as the explanatory variables. Spatial factors are also considered in the modeling since the closer the distance, the higher the correlation. This study uses the secondary data from BPS (Badan Pusat Statistik). The data will be analyzed using Moran I test, to obtain the information about spatial dependence, and using Spatial Autoregressive modeling to obtain the information, which variables are significant affecting UR and how great the influence of the spatial factors. The result is, variables proportion of married people, rate of disease, and population size are related significantly to UR. In all three regions, the Hotspot of unemployed will also be detected districts/cities using Spatial Scan Statistics Method. The results are 22 districts/cities as a regional group with the highest unemployed (Most likely cluster) in the study area; 2 districts/cities as a regional group with the highest unemployed in West Java; 1 district/city as a regional groups with the highest unemployed in Central Java; 15 districts/cities as a regional group with the highest unemployed in East Java.
KW - moran I test
KW - spatial autoregressive
KW - spatial factor
KW - spatial scan statistics
UR - http://www.scopus.com/inward/record.url?scp=84984555004&partnerID=8YFLogxK
U2 - 10.1063/1.4940866
DO - 10.1063/1.4940866
M3 - Conference contribution
AN - SCOPUS:84984555004
T3 - AIP Conference Proceedings
BT - Proceedings of the 7th SEAMS UGM International Conference on Mathematics and Its Applications 2015
A2 - Susanti, Yeni
A2 - Wijayanti, Indah Emilia
A2 - Kusumo, Fajar Adi
A2 - Aluicius, Irwan Endrayanto
PB - American Institute of Physics Inc.
T2 - 7th SEAMS UGM International Conference on Mathematics and Its Applications: Enhancing the Role of Mathematics in Interdisciplinary Research
Y2 - 18 August 2015 through 21 August 2015
ER -
