Indonesian Journal of Electrical Engineering and Computer Science Vol. 15, No. 3, September 2019, pp. 1615~1620 ISSN: 2502-4752, DOI: 10.11591/ijeecs.v15.i3.pp1615-1620  1615 Journal homepage: http://iaescore.com/journals/index.php/ijeecs A predictive model for prediction of heart surgery procedure Aufzalina Mohd Yusof 1 , Nor Azura Md. Ghani 2 , Khairul Asri Mohd Ghani 3 , Khairul Izan Mohd Ghani 4 1,2 Center for Statistical and Decision Sciences Studies, Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA, Malaysia 3 Department of Surgery, Faculty of Medicine & Health Sciences, Universiti Putra Malaysia, Malaysia 4 Columbia Asia Malaysia, Malaysia Article Info ABSTRACT Article history: Received Oct 1, 2018 Revised Dec 22, 2018 Accepted Jan 25, 2019 Coronary heart disease (CHD) is a disease in which plague in the form of waxy substance builds up inside the coronary arteries. Coronary artery bypass grafting (CABG) is used as treatment on CHD patients but the role of CABG has been challenged by percutaneous coronary intervention (PCI) when it was introduced in 1977. Drug eluting stents (DES) was introduced with the development of PCI. The purpose of this study was to find the potential risk factors that associated with the procedures (CABG and DES) and to model procedure (CABG vs DES) on coronary heart disease male patients aged 45 years old and below. The study sample was among male patients aged 45 years old and below who has undergone CABG or DES procedure at either IJN or HUKM from January 2007 until December 2010. Logistic regression was used to model treatment selection on coronary heart disease with 87.3% of the classification rate. Patient who i) smoke, ii) obese, or ii) had dyslipidemia was significantly associated with DES, and the other factors were prone to have CABG as their treatment. Keywords: Binary logistic regression CABG CHD Coronary heart disease DES Copyright © 2019 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Nor Azura Md. Ghani, Center for Statistical and Decision Sciences Studies, Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia. Email: azura@tmsk.uitm.edu.my 1. INTRODUCTION Coronary heart disease (CHD) is a disease in which plague in the form of waxy substance builds up inside the coronary arteries, whereby oxygen-rich blood will be supplied to heart muscle by these arteries [1]. The plague can break open (rupture) or hardened over time. If ones suffer with ruptured plague, the blood clot will be formed on its surfaces and this can disturb the blood flow through coronary artery. Nevertheless, the hardened plague that is built over time can narrow the artery system and blood flow will be reduced or blocked. If the flow of oxygen-rich blood to heart muscle is not sufficient, angina (chest pain) or heart attack can occur. Ones will feel like pressure or squeezing in the chest or may even feel like indigestion. The pain also can be felt at shoulders, arms, neck or back. Without quick treatments, CHD can lead to serious heart problem like heart failure, in which the heart fails to pump enough blood to meet the body needs. For almost half of century, coronary artery bypass grafting (CABG) has been regarded as the most effective revascularization treatment and become a standard care for CHD patients [2]. However, the role of CABG has been challenged over the last two decades by percutaneous coronary intervention (PCI) when it started to be introduced in 1977. Due to the increasing number of heart disease globally, several studies has been conducted that focus on the diagnostic system [3-5]. As up to date numerous studies have been conducted for the purpose of comparing the effectiveness of PCI with CABG