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All Journal UNP Journal of Statistics and Data Science
Futiah Salsabila
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences

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Classification of Stroke Disease at Dr. Drs. M. Hatta Brain Hospital Bukittinggi With Decision Tree Algorithm C4.5 Futiah Salsabila; Zamahsary Martha; Atus Amadi Putra; Admi Salma
UNP Journal of Statistics and Data Science Vol. 2 No. 1 (2024): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol2-iss1/135

Abstract

Stroke is a health condition that has vascular disorders where brain  function is related to problems with blood vessels that carry blood to the brain. Several factors that can influence stroke include unhealthy eating habits, lack of physical activity, smoking behavior, alcohol consumption, and obesity. The symptoms experienced are headache, nausea, vomiting, blurred vision and difficulty swallowing. The researcher’s aim is to determine the risk faktors that affect the incidence of stroke hospitalization based on stroke diagnoses at Rumah Sakit Otak Dr. Drs. M. Hatta Bukittinggi city by classifying each variable using a decision tree. A decision tree is a flowchart that resembles a branching tree. The C4.5 algorithm is used in this research, which can process numerical and categorical data, can handle missing attribute values, and produces rules that are easy to interpret. The results of the analysis show that the attribute that is a risk factor for stroke is the heart. The model created using the C4.5 algorithm was tested using a counfusion matrix resulting in an accuracy of 64.54%, a precision of 53.34% for classifying ischemic stroke patients correctly, and a recall of 72.73% for classifying hemorrhagic patients correctly.  
Co-Authors Admi Salma Atus Amadi Putra Zamahsary Martha