MODELING LIFE EXPECTANCY IN CENTRAL JAVA USING SPATIAL DURBIN MODEL
Central Java in 2017 was one of the provinces with high life expectancy, ranking second. Life expectancy of Central Java Province in 2017 is 74.08% per year. The fields of education, health and socio-economics, are several factors that are thought to influence the life expectancy in an area. To find...
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Universitas Diponegoro
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doaj-10f9a20b18ed4a0cbf85294b85c7b6f72020-11-25T03:40:40ZengUniversitas DiponegoroMedia Statistika1979-36932477-06472019-12-0112215216310.14710/medstat.12.2.152-16316030MODELING LIFE EXPECTANCY IN CENTRAL JAVA USING SPATIAL DURBIN MODELArief Rachman Hakim0Hasbi Yasin1Agus Rusgiyono2Departemen Statistika, Universitas DiponegoroDepartemen Statistika, FSM, Universitas DiponegoroDepartemen Statistika, FSM, Universitas DiponegoroCentral Java in 2017 was one of the provinces with high life expectancy, ranking second. Life expectancy of Central Java Province in 2017 is 74.08% per year. The fields of education, health and socio-economics, are several factors that are thought to influence the life expectancy in an area. To find out what factors that the regression analysis method can use to find out what factors influence the life expectancy. But in observations found data that have a spatial effect (location) called spatial data, a spatial regression method was developed such as linear regression analysis by adding spatial effects. One form of spatial regression is Spatial Durbin Model (SDM) which has a form like the Spatial Autoregressive Model (SAR). The difference between the two if in the SAR model the effect of spatial lag taken into account in the model is only on the response variable (Y) but in the SDM method, effect of spatial lag on the predictor variable (X) and response (Y) are also taken into account. Selection of the best model using Mean Square Error (MSE), obtained by the MSE value of 1.156411, the number mentioned is relatively small 0, which indicates that the model is quite good.https://ejournal.undip.ac.id/index.php/media_statistika/article/view/24668 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Arief Rachman Hakim Hasbi Yasin Agus Rusgiyono |
spellingShingle |
Arief Rachman Hakim Hasbi Yasin Agus Rusgiyono MODELING LIFE EXPECTANCY IN CENTRAL JAVA USING SPATIAL DURBIN MODEL Media Statistika |
author_facet |
Arief Rachman Hakim Hasbi Yasin Agus Rusgiyono |
author_sort |
Arief Rachman Hakim |
title |
MODELING LIFE EXPECTANCY IN CENTRAL JAVA USING SPATIAL DURBIN MODEL |
title_short |
MODELING LIFE EXPECTANCY IN CENTRAL JAVA USING SPATIAL DURBIN MODEL |
title_full |
MODELING LIFE EXPECTANCY IN CENTRAL JAVA USING SPATIAL DURBIN MODEL |
title_fullStr |
MODELING LIFE EXPECTANCY IN CENTRAL JAVA USING SPATIAL DURBIN MODEL |
title_full_unstemmed |
MODELING LIFE EXPECTANCY IN CENTRAL JAVA USING SPATIAL DURBIN MODEL |
title_sort |
modeling life expectancy in central java using spatial durbin model |
publisher |
Universitas Diponegoro |
series |
Media Statistika |
issn |
1979-3693 2477-0647 |
publishDate |
2019-12-01 |
description |
Central Java in 2017 was one of the provinces with high life expectancy, ranking second. Life expectancy of Central Java Province in 2017 is 74.08% per year. The fields of education, health and socio-economics, are several factors that are thought to influence the life expectancy in an area. To find out what factors that the regression analysis method can use to find out what factors influence the life expectancy. But in observations found data that have a spatial effect (location) called spatial data, a spatial regression method was developed such as linear regression analysis by adding spatial effects. One form of spatial regression is Spatial Durbin Model (SDM) which has a form like the Spatial Autoregressive Model (SAR). The difference between the two if in the SAR model the effect of spatial lag taken into account in the model is only on the response variable (Y) but in the SDM method, effect of spatial lag on the predictor variable (X) and response (Y) are also taken into account. Selection of the best model using Mean Square Error (MSE), obtained by the MSE value of 1.156411, the number mentioned is relatively small 0, which indicates that the model is quite good. |
url |
https://ejournal.undip.ac.id/index.php/media_statistika/article/view/24668 |
work_keys_str_mv |
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