{"title":"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","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":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"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\":null,\"pages\":null},\"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}","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}
Does the Physical Type of House Still Affect Household Poverty in Indonesia? An Entropy-based Fuzzy Weighted Logistic Regression Approach
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.
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