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All Journal Unisda Journal of Mathematics and Computer Science (UJMC)
Galuh Tyasing Swatika
Universitas Nahdlatul Ulama Blitar
Computer Science & IT Education Mathematics

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Analisis Regresi Logistik Untuk Mengidentifikasi Faktor-faktor Risiko Penyakit Gagal Ginjal Kronik Pada Generasi Z di Universitas Nahdlatul Ulama Blitar Ellisa Nur Fitria; Galuh Tyasing Swatika; Ewing Rudita Arini; Ardhi Sanwidi
UJMC (Unisda Journal of Mathematics and Computer Science) Vol 11 No 1 (2025): Unisda Journal of Mathematics and Computer Science
Publisher : Mathematics Department, Faculty of Sciences and Technology Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v11i1.10346

Abstract

Kidney failure is a condition in which kidney function does not work properly due to damage to the organ. In the Blitar region, the number of kidney failure patients in 2024 will fluctuate, with cases of chronic kidney failure not only experienced by the elderly, but also by young people. Therefore, this study focuses on generation Z as the main subject. The ordinal logistic regression model formed for the risk level of chronic kidney failure in generation Z at Nahdlatul Ulama University Blitar Class of 2021, namely: Logit 1 [P(Y<= 0|X)=-5,466-3,937 X6(0)-3,656 X6(1) and Logit 2 [P(Y<= 0|X)=-0,412-3,937 X6(0)-3,656 X6(0). Based on the results of the ordinal logistic regression analysis that has been carried out, it can be concluded that the variable that significantly influences the risk level of kidney failure in generation Z at Nahdlatul Ulama University, Blitar, Class of 2021 is the variable of the habit of holding urine (X6).
Co-Authors Ardhi Sanwidi Ellisa Nur Fitria EWING RUDITA ARINI