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Title : Application of Geographically Weighted Regression for Vulnerable Area Mapping of Leptospirosis in Bantul District
Author :

Dr. Prima Widayani, S.Si., M.Si. (1) Prof. Dr. Totok Gunawan, M.S. (2) Prof. Drs. Projo Danoedoro, M.Sc., Ph.D. (3)
Date : 0 2016
Keyword : Leptospirosis,Geographically Weighted Regression,Vulnerability Leptospirosis,Geographically Weighted Regression,Vulnerability
Abstract : Geographically Weighted Regression (GWR) is regression model that developed for data modeling with continuous respond variable and considering the spatial or location aspect. Leptospirosis case happened in some regions in Indonesia, including in Bantul District, Special Region of Yogyakarta. The purpose of this study are to determine local and global variable in making vulnerable area model of Leptospirosis disease, determine the best type of weighting function and make vulnerable area map of Leptospirosis. Alos satelite imagery as primary data to get settlement and paddy fields area. The others variable are the percentage of population’s age, flood risk, and the number of health facility that obtained from secondary data. Determinant variables that affect locally are flood risk, health facility, percentage of age 25-50 years old and the percentage of settlement area. Meanwhile, independent variable that affects globally is the percentage of paddy fields area. Vulnerability map of Leptospirosis disease resulted from the best GWR model which used weighting function Fixed Bisquare. There are 3 vulnerable area of Leptospirosis disease, high vulnerability area located in the middle of Bantul District, meanwhile the medium and low vulnerability area showed clustered pattern in the side of Bantul District.
Group of Knowledge : Geografi
Original Language : English
Level : Internasional
Status :
Published
Document
No Title Document Type Action
1 PrimaWidayani_TotokGunawan_Danoedoro_Martohusodo_IJG_17601-35610-1-PB.pdf
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2 Editor IJG.pdf
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3 Cover.pdf
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4 Cover belakang.pdf
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5 Subject Index.pdf
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6 Author Index.pdf
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7 CEK SIMILARITY - Above-ground carbon stock estimates of rubber (hevea brasiliensis).pdf
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8 SUKET PUBLIKASI PRIMA IJG DES 2018.pdf
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9 prima widayani lembar pengesahan lulus.pdf
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10 Similarity_Application of Geographically Weighted Regression-1.pdf
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