Logit and Complementary Log-Log Modeling in the Case of Factors Affecting Heart Failure Disease

Abstrak

Heart failure is a disease that causes a high mortality rate in the world of health. Heart disease is a disease caused by plaque that builds up in the coronary arteries that supply oxygen to the heart muscle. Research on heart failure disease aims to find out what factors affect heart failure disease and how much influence it has. This test was conducted using logistic regression method with logit modeling and complementary log-log modeling in analyzing data of 918 patients with heart failure disease. This study also takes which modeling is the best. The results of this analysis show that Age, Gender, Blood Sugar and Chest Pain affect Heart Disease.  And it is found that Logit modeling is the best modeling based on the lower AIC value than the Complementary Log-Log modeling which is 897.43.