IMPLEMENTASI METODE GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) PADA KASUS DIARE BALITA DI PROVINSI JAWA TIMUR

Felina Chantika Putri, NI Luh Putu Suciptawati, M. Susilawati
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Abstract

Spatial regression is an extension of classical regression analysis by considering spatial elements of spatial elements. One of the model of spatial regressions is the Geographically Weighted Regression (GWR). In the analysis, the GWR method considers the differences in characteristics between regions (spatial heterogeneity). Diarrhea cases in toddlers can be modeled using the GWR model. This research aims to model and identify factors that significantly influence diarrhea cases in toddlers in each district in East Java Province in 2020 using GWR. There are two weighting functions used in this research that are fixed bisquare kernel and adaptive bisquare kernel. The results showed that the GWR model with the adaptive kernel bisquare weighting function was more suitable because it produced the highest 𝑅 2 value of 79.29%. The factors that have a significant effect in each district are different and the dominant factor is the provision of vitamin A to toddlers.
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实施方法
空间回归是对经典回归分析的扩展,考虑空间元素的空间元素。其中一种空间回归模型是地理加权回归(GWR)。在分析中,GWR方法考虑了区域间特征的差异(空间异质性)。幼儿腹泻病例可以使用GWR模型建模。本研究旨在利用GWR对2020年东爪哇省各区幼儿腹泻病例进行建模并确定显著影响因素。本文采用了固定双方核和自适应双方核两种加权函数。结果表明,采用自适应核二方加权函数的GWR模型能产生最高的𝑅2值(79.29%),是最合适的模型。在每个地区有显著影响的因素是不同的,主要因素是向幼儿提供维生素a。
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审稿时长
24 weeks
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