The Clustering of Households in Madura Based on Factors Affecting Their Ingestion of Clean Water Using Similarity Weight and Filter Method

Astarani Wili Martha, I. Zain
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引用次数: 1

Abstract

Clean Water and Sanitation is one of SDGs’ indicators that relates to human’ demand for clean water. Three of four regencies in Madura Island reportedly have suffered in drought, thus it leads this research to fulfill Madura people need of water. Madura Island has 3097 households in need of water. However, not all households could fetch their need. This research aims to classify the households of Madura Island regarding factors which affect their ingestion of clean water using cluster analysis. There are clustering numerical data and categorical data. Therefore, this research uses Similarity Weight and Filter Method. SWFM is one of clustering mix methods in which there are clustering numerical, using hierarchical ward, and clustering categorical, using k-modes. To analyze the clustering numerical data, there are 3 variables and it gains two optimum groups by using ward method with pseudo-F 1001,172. Clustering categorical analysis uses 6 variables with k-modes and gains three groups and SWFM gains five groups. Five groups are selected because they produced the smallest ratio 0,006627 in the group.
基于相似权重和过滤法对马杜拉市居民饮用净水影响因素的聚类研究
清洁水和卫生设施是与人类对清洁水的需求有关的可持续发展目标指标之一。据报道,马杜拉岛四分之三的地区遭受干旱,因此这项研究是为了满足马杜拉人对水的需求。马杜拉岛有3097户家庭需要水。然而,并非所有家庭都能满足他们的需求。本研究的目的是利用聚类分析对马杜拉岛的家庭进行分类,以了解影响他们摄取清洁水的因素。有聚类数值数据和分类数据。因此,本研究采用相似度权重和过滤方法。SWFM是一种混合聚类方法,其中有数值聚类和分类聚类。对聚类数值数据进行分析,有3个变量,采用伪f11,172的ward方法得到两个最优组。聚类分类分析使用6个具有k模式的变量,获得3组,SWFM获得5组。选择5个组是因为它们在组中产生的比率最小,为0 000 6627。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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