Distance and Areas Weighting of GWR Kriging for Stunting Cases In East Java

Spatial heterogeneity shows the characteristic location from one location to others location and it is the main assumption in Geographically Weighted Regression.  The location becomes a weight on GWR model, There are two groups of location weight namely based on distance and area. The weight conside...

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Published in:Cauchy Vol. 6; no. 4; pp. 212 - 217
Main Authors: Ardianti, Deby, Pramoedyo, Henny, Nurjannah, Nurjannah
Format: Journal Article
Language:English
Published: Mathematics Department UIN Maulana Malik Ibrahim Malang 30.05.2021
Subjects:
analisis spasial
statistika
ISSN:2086-0382, 2477-3344
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Abstract Spatial heterogeneity shows the characteristic location from one location to others location and it is the main assumption in Geographically Weighted Regression.  The location becomes a weight on GWR model, There are two groups of location weight namely based on distance and area. The weight considers the closeness between the location. The accuracy weighted is needed because the weighting represents the data location. The aim of this research was to get a suitable weighting method for stunting data. This research used secondary data about stunting and the influence factors of stunting such as coverage visiting of pregnant women (K1), consumption of FE tablet, exclusive of breastfeeding, immunization coverage, and clean health behaviour. Those data obtained from the Healthy Ministry of East Jawa.Based on the results of this research show that the goodness weighting for GWR modell is Adaptive Bisquare Kernel (distance weighting). The predicted mapping stunting is showed by interpolation Kriging with a range of 27%  to 49,5%.
AbstractList Spatial heterogeneity shows the characteristic location from one location to others location and it is the main assumption in Geographically Weighted Regression.  The location becomes a weight on GWR model, There are two groups of location weight namely based on distance and area. The weight considers the closeness between the location. The accuracy weighted is needed because the weighting represents the data location. The aim of this research was to get a suitable weighting method for stunting data. This research used secondary data about stunting and the influence factors of stunting such as coverage visiting of pregnant women (K1), consumption of FE tablet, exclusive of breastfeeding, immunization coverage, and clean health behaviour. Those data obtained from the Healthy Ministry of East Jawa.Based on the results of this research show that the goodness weighting for GWR modell is Adaptive Bisquare Kernel (distance weighting). The predicted mapping stunting is showed by interpolation Kriging with a range of 27%  to 49,5%.
Author Ardianti, Deby
Nurjannah, Nurjannah
Pramoedyo, Henny
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statistika
Title Distance and Areas Weighting of GWR Kriging for Stunting Cases In East Java
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