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All Journal Unisda Journal of Mathematics and Computer Science (UJMC) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Journal of Science Nusantara
EWING RUDITA ARINI
Universitas Nahdlatul Ulama Blitar
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Mathematics Mechanical Engineering

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Journal : Unisda Journal of Mathematics and Computer Science (UJMC)

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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).
Analisis Faktor Acute Flaccid Paralysis Di Provinsi Jawa Timur Menggunakan Regresi Poisson Inverse Gaussian Ma'rifatul Julviana; Rizka Rizqi Robby; Galuh Tyasing Swastika; Ewing Rudita Arini
UJMC (Unisda Journal of Mathematics and Computer Science) Vol 11 No 2 (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.v11i2.10591

Abstract

Acute Flaccid Paralysis (AFP) is a paralysis condition that occurs suddenly and is weak, usually experienced by children under 15 years of age and is not caused by an accident. In 2005, Indonesia experienced its first case of the polio virus, when it almost received an international polio-free certificate. East Java Province, as one of the provinces with the largest population in Indonesia, has big challenges in controlling AFP cases. In this study there were 7 variables used including 1 dependent variable, namely the number of cases of Acute Flaccid Paralysis (AFP), and 6 independent variables including Population Density (), Percentage of Polio Immunization (), Number of Health Workers (), Percentage of Clean Water Availability (), Number of Poor Population (), and Human Development Index (HDI) (). In this research data, the variance value is much greater than the average (overdispersion), so to handle this, the Poisson inverse Gaussian regression method is used because it is very suitable for dealing with count data that experiences overdispersion. The best modeling form of Poisson inverse Gaussian regression for the number of AFP cases in East Java Province is as follows:. Based on hypothesis testing, the factors that have the most influence on the best model of AFP cases in East Java Province using Poisson inverse Gaussian (PIG) ​​regression are the Percentage of Polio Immunization (), and the Number of Health Workers (
Co-Authors Amania, Fiki Ardhi Sanwidi Ellisa Nur Fitria Elmasari, Yandria Galuh Tyasing Swastika Galuh Tyasing Swatika Hakim, Muhammad Helmi Khuluqi, Ahmad Machbubil Laili, Azizatul Ma'rifatul Julviana Mustofa, Muhammad Fikri Aziz Ngabidin, Zaenal Nurhadi Rizka Rizqi Robby Robby, Rizka Rizqi Sanwidi, Ardhi Ulfa Niswatul