CLASSIFICATION OF STUNTING USING GEOGRAPHICALLY WEIGHTED REGRESSION-KRIGING CASE STUDY: STUNTING IN EAST JAVA
Geographically Weighted Regression Kriging (GWRK) is a special case of Geographically Weighted Regression (GWR) model, which is modeling with the effect of spatial autocorrelation on the GWR model error. The purpose of this research is to obtain a GWRK model between the factors that affect stunting...
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Universitas Pattimura
2023-04-01
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| Series: | Barekeng |
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7638 |
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| author | Atiek Iriany Wigbertus Ngabu Danang Arianto Arditama Putra |
| author_facet | Atiek Iriany Wigbertus Ngabu Danang Arianto Arditama Putra |
| author_sort | Atiek Iriany |
| collection | DOAJ |
| description | Geographically Weighted Regression Kriging (GWRK) is a special case of Geographically Weighted Regression (GWR) model, which is modeling with the effect of spatial autocorrelation on the GWR model error. The purpose of this research is to obtain a GWRK model between the factors that affect stunting density for each site viewed from the district center point in East Java Province and to make a prediction map based on the GWRK modeling. The data used was obtained from Basic Health Research (RISKESDAS) and the East Java Health Profile Book for 2021. The units of observation in this study were 38 districts in East Java.. Based on the GWR modeling results, it was found that the GWR model error contained spatial autocorrelation so that GWR model can be formed. From the GWRK modeling using stunting prevalence data in East Java in 2021, it was found that the GWR model was better than the global regression. Through prediction and prediction mapping formed from the GWR-Kriging modeling, it could be seen that stunting in regencies in East Java was evenly distributed . The interpolation map showed that the stunting forecasting values using the Kriging GWR interpolation ranged from 27% to 46%. |
| format | Article |
| id | doaj-art-2a91bf3cdc234128a504c33639ec3771 |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2023-04-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-2a91bf3cdc234128a504c33639ec37712025-08-20T03:35:56ZengUniversitas PattimuraBarekeng1978-72272615-30172023-04-011710495050410.30598/barekengvol17iss1pp0495-05047638CLASSIFICATION OF STUNTING USING GEOGRAPHICALLY WEIGHTED REGRESSION-KRIGING CASE STUDY: STUNTING IN EAST JAVAAtiek Iriany0Wigbertus Ngabu1Danang Arianto2Arditama Putra3Department Statistics, Faculty Mathematics and Science, Brawijaya University, IndonesiaDepartment Statistics, Faculty Mathematics and Science, Brawijaya University, IndonesiaDepartment Statistics, Faculty Mathematics and Science, Brawijaya University, IndonesiaDepartment Statistics, Faculty Mathematics and Science, Brawijaya University, IndonesiaGeographically Weighted Regression Kriging (GWRK) is a special case of Geographically Weighted Regression (GWR) model, which is modeling with the effect of spatial autocorrelation on the GWR model error. The purpose of this research is to obtain a GWRK model between the factors that affect stunting density for each site viewed from the district center point in East Java Province and to make a prediction map based on the GWRK modeling. The data used was obtained from Basic Health Research (RISKESDAS) and the East Java Health Profile Book for 2021. The units of observation in this study were 38 districts in East Java.. Based on the GWR modeling results, it was found that the GWR model error contained spatial autocorrelation so that GWR model can be formed. From the GWRK modeling using stunting prevalence data in East Java in 2021, it was found that the GWR model was better than the global regression. Through prediction and prediction mapping formed from the GWR-Kriging modeling, it could be seen that stunting in regencies in East Java was evenly distributed . The interpolation map showed that the stunting forecasting values using the Kriging GWR interpolation ranged from 27% to 46%.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7638stuntinggwrgwr-kriging |
| spellingShingle | Atiek Iriany Wigbertus Ngabu Danang Arianto Arditama Putra CLASSIFICATION OF STUNTING USING GEOGRAPHICALLY WEIGHTED REGRESSION-KRIGING CASE STUDY: STUNTING IN EAST JAVA Barekeng stunting gwr gwr-kriging |
| title | CLASSIFICATION OF STUNTING USING GEOGRAPHICALLY WEIGHTED REGRESSION-KRIGING CASE STUDY: STUNTING IN EAST JAVA |
| title_full | CLASSIFICATION OF STUNTING USING GEOGRAPHICALLY WEIGHTED REGRESSION-KRIGING CASE STUDY: STUNTING IN EAST JAVA |
| title_fullStr | CLASSIFICATION OF STUNTING USING GEOGRAPHICALLY WEIGHTED REGRESSION-KRIGING CASE STUDY: STUNTING IN EAST JAVA |
| title_full_unstemmed | CLASSIFICATION OF STUNTING USING GEOGRAPHICALLY WEIGHTED REGRESSION-KRIGING CASE STUDY: STUNTING IN EAST JAVA |
| title_short | CLASSIFICATION OF STUNTING USING GEOGRAPHICALLY WEIGHTED REGRESSION-KRIGING CASE STUDY: STUNTING IN EAST JAVA |
| title_sort | classification of stunting using geographically weighted regression kriging case study stunting in east java |
| topic | stunting gwr gwr-kriging |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7638 |
| work_keys_str_mv | AT atiekiriany classificationofstuntingusinggeographicallyweightedregressionkrigingcasestudystuntingineastjava AT wigbertusngabu classificationofstuntingusinggeographicallyweightedregressionkrigingcasestudystuntingineastjava AT danangarianto classificationofstuntingusinggeographicallyweightedregressionkrigingcasestudystuntingineastjava AT arditamaputra classificationofstuntingusinggeographicallyweightedregressionkrigingcasestudystuntingineastjava |