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All Journal Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Uci Lestari, Tri
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Computer Science & IT Engineering Mechanical Engineering Transportation

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Application of Binary Logistic Regression Method in Diagnosing Ischemic Stroke Disease at Petala Bumi Hospital, Riau Province Marizal, Muhammad; Uci Lestari, Tri
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 1 No. 1 (2024)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v1i1.34099

Abstract

Stroke occurs suddenly when blood flow is obstructed while supplying blood to the brain. Ischemic stroke is a type of stroke that often occurs and is a major cause of disability and even death. The large number of ischemic stroke incidents is the result of ignorance of the risk factors that lead to the emergence of ischemic stroke events. The purpose of this study was to determine the risk factors that significantly influence ischemic stroke and to determine the chances of thrombotic and embolic ischemic stroke by involving several independent variables. Factors that are thought to influence the occurrence of ischemic stroke in this study were age, gender, hypertension status, diabetes mellitus status, hypercholesterolemia status, obesity, triglycerides, body mass indeks, diet, and smoking habits. The method used in this research is binary logistic regression. The results of the analysis show that age and hypertension status have a significant effect on ischemic stroke with a classification accuracy of 74% the rest is influenced by other factors
Co-Authors M Marizal