📅 14 July 2025
DOI: 10.62951/ijamc.v2i3.222
Identification of Risk Factors for Chronic Kidney Disease Using Binary Logistic Regression
International Journal of Applied Mathematics and Computing
Asosiasi Riset Ilmu Matematika dan Sains Indonesia (ARIMSI)
📄 Abstract
Chronic Kidney Disease (CKD) is a major global health issue that can lead to serious complications and long-term medical care. This study aims to identify key clinical factors associated with CKD status using binary logistic regression analysis. The dataset, obtained from Kaggle, contains 400 patient records with various clinical and demographic attributes. The dependent variable is CKD status (positive or negative), while the independent variables include age, blood pressure, hemoglobin level, urine albumin level, and serum creatinine. Initial analysis involved descriptive statistics and multicollinearity checks, followed by model estimation and evaluation using likelihood ratio and Wald tests. The final model identified four significant predictors: blood pressure, hemoglobin, urine albumin, and serum creatinine. The model achieved a high classification accuracy of 95.50% and an Area Under the ROC Curve (AUC) of 98.78%, indicating excellent predictive performance. These results highlight the importance of these clinical indicators in early CKD detection and support their use in risk assessment models for kidney disease screening
Keywords: Chronic Kidney Disease, Binary Logistic Regression, Likelihood Ratio Test, Wald Test, Classification Accuracy
Keywords: Chronic Kidney Disease, Binary Logistic Regression, Likelihood Ratio Test, Wald Test, Classification Accuracy
🔖 Keywords
#Chronic Kidney Disease; Binary Logistic Regression; Likelihood Ratio Test; Wald Test; Classification Accuracy
ℹ️ Informasi Publikasi
Tanggal Publikasi
14 July 2025
Volume / Nomor / Tahun
Volume 2, Nomor 3, Tahun 2025
📝 HOW TO CITE
Kosasih, Eva; Asmara Santhi, Ni Kadek Wulanda; Febriyanti, Ni Wayan Atik; Br Barus, Eka Valencia; Susilawati, Made, "Identification of Risk Factors for Chronic Kidney Disease Using Binary Logistic Regression," International Journal of Applied Mathematics and Computing, vol. 2, no. 3, Jul. 2025.
ACM
ACS
APA
ABNT
Chicago
Harvard
IEEE
MLA
Turabian
Vancouver
Download Citation
0
Sitasi
Cek Google Scholar