Bandwidth Modelling on Geographically Weighted Regression with Bisquare Adaptive Method using Kriging Interpolation for Land Price Estimation Model

Land prices, especially in an urban area, are dynamically changing.  To be able to do an evaluation, the right models must have the ability to understand land price characteristics that also dynamically changing. Every land price must attach to a location (spatial based). One of the locations (spati...

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Main Authors: Alfita Puspa Handayani, Albertus Deliar, Irawan Sumarto, Ibnu Syabri
Format: Article
Language:English
Published: Universitas Gadjah Mada 2020-04-01
Series:Indonesian Journal of Geography
Subjects:
gwr
Online Access:https://jurnal.ugm.ac.id/ijg/article/view/43724
id doaj-89a303ee6e1b4c00a8231e43c83402c5
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spelling doaj-89a303ee6e1b4c00a8231e43c83402c52020-11-25T01:53:47ZengUniversitas Gadjah MadaIndonesian Journal of Geography0024-95212354-91142020-04-01521364110.22146/ijg.4372426726Bandwidth Modelling on Geographically Weighted Regression with Bisquare Adaptive Method using Kriging Interpolation for Land Price Estimation ModelAlfita Puspa Handayani0Albertus Deliar1Irawan Sumarto2Ibnu Syabri3Faculty of Earth Science and Technology, Institut Teknologi Bandung, Indonesia.Faculty of Earth Science and Technology, Institut Teknologi Bandung, Indonesia.Faculty of Earth Science and Technology, Institut Teknologi Bandung, Indonesia.Faculty of Earth Science and Technology, Institut Teknologi Bandung, Indonesia.Land prices, especially in an urban area, are dynamically changing.  To be able to do an evaluation, the right models must have the ability to understand land price characteristics that also dynamically changing. Every land price must attach to a location (spatial based). One of the locations (spatial based) models is Geographically Weighted Regression (GWR). This model can provide a local model based on the concept of attachment between observation and regression points. The main component is the determination of Optimum Bandwidth, which will determine the accuracy of the final GWR model. In the bandwidth process, it is necessary to do trial and error to get the Optimum Bandwidth value. Cross-Validation method commonly used to determine optimum bandwidth on observation point, but this study aims to minimize the process of trial and error in determining optimal bandwidth outside the observation point by using kriging interpolation. The Kriging method can substantially provide better bandwidth usage without having to do a trial process with too many errors.https://jurnal.ugm.ac.id/ijg/article/view/43724land pricekriginggwrinterpolationbandwidth
collection DOAJ
language English
format Article
sources DOAJ
author Alfita Puspa Handayani
Albertus Deliar
Irawan Sumarto
Ibnu Syabri
spellingShingle Alfita Puspa Handayani
Albertus Deliar
Irawan Sumarto
Ibnu Syabri
Bandwidth Modelling on Geographically Weighted Regression with Bisquare Adaptive Method using Kriging Interpolation for Land Price Estimation Model
Indonesian Journal of Geography
land price
kriging
gwr
interpolation
bandwidth
author_facet Alfita Puspa Handayani
Albertus Deliar
Irawan Sumarto
Ibnu Syabri
author_sort Alfita Puspa Handayani
title Bandwidth Modelling on Geographically Weighted Regression with Bisquare Adaptive Method using Kriging Interpolation for Land Price Estimation Model
title_short Bandwidth Modelling on Geographically Weighted Regression with Bisquare Adaptive Method using Kriging Interpolation for Land Price Estimation Model
title_full Bandwidth Modelling on Geographically Weighted Regression with Bisquare Adaptive Method using Kriging Interpolation for Land Price Estimation Model
title_fullStr Bandwidth Modelling on Geographically Weighted Regression with Bisquare Adaptive Method using Kriging Interpolation for Land Price Estimation Model
title_full_unstemmed Bandwidth Modelling on Geographically Weighted Regression with Bisquare Adaptive Method using Kriging Interpolation for Land Price Estimation Model
title_sort bandwidth modelling on geographically weighted regression with bisquare adaptive method using kriging interpolation for land price estimation model
publisher Universitas Gadjah Mada
series Indonesian Journal of Geography
issn 0024-9521
2354-9114
publishDate 2020-04-01
description Land prices, especially in an urban area, are dynamically changing.  To be able to do an evaluation, the right models must have the ability to understand land price characteristics that also dynamically changing. Every land price must attach to a location (spatial based). One of the locations (spatial based) models is Geographically Weighted Regression (GWR). This model can provide a local model based on the concept of attachment between observation and regression points. The main component is the determination of Optimum Bandwidth, which will determine the accuracy of the final GWR model. In the bandwidth process, it is necessary to do trial and error to get the Optimum Bandwidth value. Cross-Validation method commonly used to determine optimum bandwidth on observation point, but this study aims to minimize the process of trial and error in determining optimal bandwidth outside the observation point by using kriging interpolation. The Kriging method can substantially provide better bandwidth usage without having to do a trial process with too many errors.
topic land price
kriging
gwr
interpolation
bandwidth
url https://jurnal.ugm.ac.id/ijg/article/view/43724
work_keys_str_mv AT alfitapuspahandayani bandwidthmodellingongeographicallyweightedregressionwithbisquareadaptivemethodusingkriginginterpolationforlandpriceestimationmodel
AT albertusdeliar bandwidthmodellingongeographicallyweightedregressionwithbisquareadaptivemethodusingkriginginterpolationforlandpriceestimationmodel
AT irawansumarto bandwidthmodellingongeographicallyweightedregressionwithbisquareadaptivemethodusingkriginginterpolationforlandpriceestimationmodel
AT ibnusyabri bandwidthmodellingongeographicallyweightedregressionwithbisquareadaptivemethodusingkriginginterpolationforlandpriceestimationmodel
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