PERBANDINGAN MATRIKS PEMBOBOT ROOK DAN QUEEN CONTIGUITY DALAM ANALISIS SPATIAL AUTOREGRESSIVE MODEL (SAR) DAN SPATIAL ERROR MODEL (SEM)

Ingka Rizkyani Akolo
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引用次数: 3

Abstract

The spatial weighting matrix is very important to overview of the relationship between one location to another in the spatial regression. In this study, the authors compare the weighting matrix of queen contiguity and rook contiguity in the SAR and SEM models in stunting cases in Bone Bolango Regency, Gorontalo Province. The variables used are the number of IDL, the percentage of LBW, the amount of proper sanitation, the percentage of exclusively breastfed babies, and the number of poor people. The purpose of this study was to determine the factors that influence stunting in Bone Bolango Regency, compare the results of the analysis of the rook contiguity and queen contiguity matrices in the SAR and SEM models and determine the best model and weighting matrix in stunting modeling in Bone Bolango Regency. The results showed that the significant factor in the SAR model was the number of poor people, while the significant factors in the SEM model were the number of IDL, the number of proper sanitation, and the percentage of exclusively breastfed babies. In the SEM model, the p-value of queen contiguity is smaller than that of rook contiguity.The best model in this study is the SEM model.
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在空间回归中,空间加权矩阵对于概览一个位置与另一个位置之间的关系非常重要。在这项研究中,作者比较了在Gorontalo省Bone Bolango Regency的发育迟缓病例的SAR和SEM模型中皇后邻近度和小鹿邻近度的权重矩阵。所使用的变量是缺乏营养的人数、低体重的百分比、适当卫生设施的数量、纯母乳喂养婴儿的百分比以及贫困人口的数量。本研究的目的是确定影响Bone Bolango Regency发育迟缓的因素,比较SAR和SEM模型中白头鹰和皇后相邻矩阵的分析结果,确定Bone Bolango Regency发育迟缓建模的最佳模型和权重矩阵。结果表明,SAR模型中的显著因素是贫困人口数量,SEM模型中的显著因素是IDL数量、适当卫生设施数量和纯母乳喂养婴儿比例。在SEM模型中,皇后相邻的p值小于车相邻的p值。本研究中最好的模型是SEM模型。
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