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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi
Yustisia, Grissila
Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang
Mathematics

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Geographically Weighted Regression (GWR) Modelling with Weighted Fixed Gaussian Kernel and Queen Contiguity for Dengue Fever Case Data Yustisia, Grissila
CAUCHY Vol 5, No 1 (2017): CAUCHY
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (746.711 KB) | DOI: 10.18860/ca.v5i1.4393

Abstract

Regression analysis is a method for determining the effect of the response and predictor variables, yet simple regression does not consider the different properties in each location. Methods Geographically Weighted Regression (GWR) is a technique point of approach to a simple regression model be weighted regression model. The purpose of this study is to establish a model using Geographically Weighted Regression (GWR) with a weighted Fixed Gaussian Kernel and Queen Contiguity in cases of dengue fever patients and to determine the best weighting between the weighted Euclidean distance as well as the Queen Contiguity based on the value of R2. Results from the study showed that the modeling Geographically Weighted Regression (GWR) with a weighted Fixed Gaussian Kernel showed that all predictor variables affect the number of dengue fever patients, whereas the weighted Queen Contiguity, not all predictor variables affect the dengue fever patients. Based on the value of R2 is known that a weighted Fixed Gaussian Kernel is better used.
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