Spatial Clustering Using Generalized LASSO on the Gender and Human Development Index in Papua Island in 2022

Ahdan Darul Mutaqin, S. Rahardiantoro, Mohammad Masjkur
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Abstract

Equitable development from a gender perspective needs attention. Based on data from the World Economic Forum (WEF), gender equality in Indonesia has increased. Even so, the island of Papua is still very low on gender equality. It can be seen from the Gender Development Index (IPG) from the Central Bureau of Statistics (BPS), there is a considerable gap between the Papua Island IPG and the National. IPG is a comparison between the Human Development Index (IPM) for Men and Women. Based on these conditions, this study aims to classify GPI, Male IPM, and Female IPM by region using the spatial clustering method in 2022. One of the analytical methods that can overcome these conditions is Generalized LASSO. Generalized LASSO can be used on data that only has a response variable (y) for clustering. Generalized LASSO clustering uses a penalty matrix D. The formation of the D matrix is formed by giving values -1 and 1 for areas that intersect or are adjacent and a value of 0 for other areas. The best clustering for IPG uses KNN with K = 3 and the number of clusters formed is 2 clusters. The best clustering for male HDI uses KNN with K = 2 and the number of clusters formed is 8. The best clustering for female HDI uses KNN with K = 2 and the number of clusters formed is 10 clusters.
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利用广义 LASSO 对 2022 年巴布亚岛的性别和人类发展指数进行空间聚类
从性别角度看公平发展需要关注。根据世界经济论坛(WEF)的数据,印度尼西亚的性别平等程度有所提高。即便如此,巴布亚岛的性别平等程度仍然很低。从中央统计局(BPS)的性别发展指数(IPG)可以看出,巴布亚岛的 IPG 与全国的 IPG 之间存在相当大的差距。IPG 是男女人类发展指数(IPM)的比较。基于这些情况,本研究旨在利用空间聚类方法,在 2022 年对各地区的 GPI、男性 IPM 和女性 IPM 进行分类。广义 LASSO 是可以克服这些条件的分析方法之一。广义 LASSO 可用于仅有一个响应变量(y)的数据聚类。广义 LASSO 聚类使用惩罚矩阵 D。D 矩阵的形成方法是,对相交或相邻的区域取值 -1 和 1,对其他区域取值 0。IPG 的最佳聚类使用 KNN,K=3,形成的聚类数为 2 个聚类。男性人类发展指数的最佳聚类使用 KNN(K = 2),形成的聚类数为 8 个。
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