利用自适应高斯核加权对印度尼西亚 GRDP 进行地理加权回归建模

Frangly Elviano Tangka, Djoni Hatidja, W. Weku
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摘要

本研究的目的是利用带有自适应高斯核加权函数的地理加权回归(GWR)确定影响2022年印度尼西亚地区国内生产总值(GRDP)的变量。本研究使用的数据来自中央统计局网站的二手数据。 使用的变量包括印尼 34 个省的地区国内生产总值(Y,单位为十亿印尼盾)、劳动力参与率(X1,单位为%)、外商投资(X2,单位为百万美元)、公开失业率(X3,单位为%)和人类发展指数(X4,单位为%)。 数据采用自适应高斯核加权函数 GWR 进行分析。苏门答腊岛上所有省份(11 个省)、雅加达省、万丹省和西加里曼丹省的 GRDP 受外商投资(X2)和人类发展指数(X4)的影响。 而其他 19 个省的 GRDP 仅受外国投资(X2)的影响。 印尼各省的自适应高斯核加权函数 GWR 模型的形成方式各不相同:自适应高斯核;GWR;地区生产总值
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Geographically Weighted Regression Modeling with Adaptive Gaussian Kernel Weighting on GRDP in Indonesia
The purpose of this study is to determine the variables that affect Gross Regional Domestic Product (GRDP) in Indonesia in 2022 using Geographically Weighted Regression (GWR) with Adaptive Gaussian kernel weighting function. The data used in this study uses secondary data taken from the website of the Central Bureau of Statistics.  The variables used are gross regional domestic product of 34 provinces in Indonesia (Y, in billion rupiah), labor force participation rate (X1, in %), foreign investment (X2, in million dollars), open unemployment rate (X3, in %) and human development index (X4, in %).  Data were analyzed using GWR with adaptive gaussian kernel weighting function. GRDP in all provinces on the island of Sumatra (11 provinces), DKI Jakarta province, Banten province, and West Kalimantan province are influenced by foreign investment (X2) and human development index (X4).  Meanwhile, GRDP in the other 19 provinces is only influenced by foreign investment (X2).  GWR model with adaptive gaussian kernel weighting function is formed differently for each province in Indonesia. Keywords: Adaptive gaussian kernel; GWR; gross regional domestic product
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