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

Authors

  • Ajiwasesa Harumeka Central Bureau of Statistics, East Java Province, Indonesia
  • Taly Purwa Central Bureau of Statistics, Bali Province, Indonesia

DOI:

https://doi.org/10.32890/jict2023.22.3.2

Keywords:

Classification, imbalanced data, poor household, weighted logistic regression

Abstract

Poverty is one of the biggest challenges facing the world nowadays. Numerous studies have concentrated on the characteristics that
determine poverty to identify poor households. One of the most important factors is the physical type of the house. The physical type
of houses includes floor type, wall type, roof type, and floor area per inhabitant in Indonesia, especially Surabaya, one of Indonesia’s big
cities and the capital of East Java Province. This factor gave promising results to the country. Therefore, it was assumed that these variables
could no longer distinguish between those in wealth and those in poverty. Poor household data are one example of imbalanced data in
terms 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.

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Published

24-07-2023

Issue

Vol. 22 No. 3 (2023): Journal of Information and Communication Technology (JICT) Vol.22, No.3, July 2023

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Articles

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How to Cite

Harumeka, A., & Purwa, T. (2023). Does the Physical Type of House Still Affect Household Poverty in Indonesia? An Entropy-based Fuzzy Weighted Logistic Regression Approach. Journal of Information and Communication Technology, 22(3), 337-361. https://doi.org/10.32890/jict2023.22.3.2

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Identifiers DOI 10.32890/jict2023.22.3.2 OpenAlex W4386103429 Semantic Scholar CorpusID 261144461 Scopus 85168599125