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

Deby Ardianti, Henny Pramoedyo, Nurjannah Nurjannah


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%.


statistika; analisis spasial

Full Text:



N. R. Draper and H. Smith, Applied regression analysis, vol. 326. John Wiley & Sons, 1998.

D. N. Gujarati, BASIC ECONOMETRICS, FOURTH. New York: McGraw-Hill Companies, INc, 2003.

M. Fischer and A. Getis, Handbook of Applied Spatial Analysis. New York: Springer, 2010.

A. S. Fotheringham, C. Brunsdon, and M. Charlton, Geographically weighted regression: the analysis of spatially varying relationships. John Wiley & Sons, 2003.

C. Chasco, “Modeling spatial variations in household disposable income with Geographically Weighted Regression,” no. January, 2007.

L. Anselin, I. Syabri, and Y. Kho, “GeoDa : An Introduction to Spatial Data Analysis,” vol. 38, pp. 5–22, 2006.

J. Walter and W. L. Jeremy, “Local and global approaches to spatial data analysis in ecology Spatial autocorrelation,” pp. 97–98, 2005.

M. Armstrong, Basic linear geostatistics. Springer Science & Business Media, 1998.

Kementerian Kesehatan RI, Situasi Balita Pendek (Stunting) di Indonesia. Jakarta: Kemenkes RI, 2019.

TNP2K, 100 Kabupaten/Kota Prioritas Untuk Intervensi Anak Kerdil (Stunting. Jakarta: TNP2K RI, 2017.

H. Pramoedyo, Analisis Spasial Dasar. Malang: Universitas Negeri Malang Press, 2017.

DOI: https://doi.org/10.18860/ca.v6i4.10455


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Editorial Office
Mathematics Department,
Universitas Islam Negeri Maulana Malik Ibrahim Malang
Jalan Gajayana 50 Malang, Jawa Timur, Indonesia 65144
Faximile (+62) 341 558933
e-mail: cauchy@uin-malang.ac.id

Creative Commons License
CAUCHY: Jurnal Matematika Murni dan Aplikasi is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.