Does the Physical Type of House Still Affect Household Poverty in Indonesia? An Entropy-based Fuzzy Weighted Logistic Regression Approach

Ajiwasesa Harumeka, Taly Purwa
{"title":"Does the Physical Type of House Still Affect Household Poverty in Indonesia? An Entropy-based Fuzzy Weighted Logistic Regression Approach","authors":"Ajiwasesa Harumeka, Taly Purwa","doi":"10.32890/jict2023.22.3.2","DOIUrl":null,"url":null,"abstract":"Poverty is one of the biggest challenges facing the world nowadays. Numerous studies have concentrated on the characteristics thatdetermine poverty to identify poor households. One of the most important factors is the physical type of the house. The physical typeof houses includes floor type, wall type, roof type, and floor area per inhabitant in Indonesia, especially Surabaya, one of Indonesia’s bigcities and the capital of East Java Province. This factor gave promising results to the country. Therefore, it was assumed that these variablescould no longer distinguish between those in wealth and those in poverty. Poor household data are one example of imbalanced data interms of classification, which is a concern. The Rare Event Weighted Logistic Regression (RE-WLR) and Entropy-based Fuzzy Weighted Logistic Regression (EFWLR) methods were utilised to overcome these problems. As a result, the only factor, including the physical design of a house, which had a substantial impact on the likelihood that a household would be classified as poor, was the floor area per capita. The other three variables were not statistically significant, namely floor type, wall type, and roof type. In addition, the elimination of the physical type of house would reduce the Area Under the Curve of the RE-WLR and EFWLR methods by 6.78 percent and 6.85 percent, respectively.","PeriodicalId":39396,"journal":{"name":"International Journal of Information and Communication Technology","volume":"164 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Information and Communication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32890/jict2023.22.3.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0

Abstract

Poverty is one of the biggest challenges facing the world nowadays. Numerous studies have concentrated on the characteristics thatdetermine poverty to identify poor households. One of the most important factors is the physical type of the house. The physical typeof houses includes floor type, wall type, roof type, and floor area per inhabitant in Indonesia, especially Surabaya, one of Indonesia’s bigcities and the capital of East Java Province. This factor gave promising results to the country. Therefore, it was assumed that these variablescould no longer distinguish between those in wealth and those in poverty. Poor household data are one example of imbalanced data interms of classification, which is a concern. The Rare Event Weighted Logistic Regression (RE-WLR) and Entropy-based Fuzzy Weighted Logistic Regression (EFWLR) methods were utilised to overcome these problems. As a result, the only factor, including the physical design of a house, which had a substantial impact on the likelihood that a household would be classified as poor, was the floor area per capita. The other three variables were not statistically significant, namely floor type, wall type, and roof type. In addition, the elimination of the physical type of house would reduce the Area Under the Curve of the RE-WLR and EFWLR methods by 6.78 percent and 6.85 percent, respectively.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
房屋的物理类型是否仍然影响印度尼西亚的家庭贫困?基于熵的模糊加权逻辑回归方法
贫困是当今世界面临的最大挑战之一。许多研究集中在决定贫困的特征上,以确定贫困家庭。最重要的因素之一是房子的物理类型。在印度尼西亚,房屋的物理类型包括地板类型,墙壁类型,屋顶类型和人均建筑面积,特别是泗水,印度尼西亚的大城市之一和东爪哇省的首府。这个因素给这个国家带来了可喜的结果。因此,假设这些变量不再能够区分富人和穷人。糟糕的家庭数据是数据分类不平衡的一个例子,这是一个令人担忧的问题。利用罕见事件加权逻辑回归(RE-WLR)和基于熵的模糊加权逻辑回归(EFWLR)方法来克服这些问题。因此,包括房屋的实际设计在内,对一个家庭被列为贫穷的可能性有重大影响的唯一因素是人均建筑面积。其他三个变量,即地板类型、墙壁类型和屋顶类型,均无统计学意义。此外,消除房屋的物理类型将使RE-WLR和EFWLR方法的曲线下面积分别减少6.78%和6.85%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
0.70
自引率
0.00%
发文量
95
期刊介绍: IJICT is a refereed journal in the field of information and communication technology (ICT), providing an international forum for professionals, engineers and researchers. IJICT reports the new paradigms in this emerging field of technology and envisions the future developments in the frontier areas. The journal addresses issues for the vertical and horizontal applications in this area. Topics covered include: -Information theory/coding- Information/IT/network security, standards, applications- Internet/web based systems/products- Data mining/warehousing- Network planning, design, administration- Sensor/ad hoc networks- Human-computer intelligent interaction, AI- Computational linguistics, digital speech- Distributed/cooperative media- Interactive communication media/content- Social interaction, mobile communications- Signal representation/processing, image processing- Virtual reality, cyber law, e-governance- Microprocessor interfacing, hardware design- Control of industrial processes, ERP/CRM/SCM
期刊最新文献
A Huffman based short message service compression technique using adjacent distance array Machine Learning Models for Behavioural Diversity of Asian Elephants Prediction Using Satellite Collar Data Visually Impaired Usability Requirements for Accessible Mobile Applications: A Checklist for Mobile E-book Applications Dengue Outbreak Detection Model Using Artificial Immune System: A Malaysian Case Study Modelling and Forecasting the Trend in Cryptocurrency Prices
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1