Comparison of Backpropagation with Nguyen Widrow in Heart Attack Classification

Abstract

— Heart disease is a disease that is often fatal and requires
early detection for more effective prevention. Classification of
heart disease through data processing techniques is an important
approach in treating this disease. In this study, heart disease
classification was carried out using two Backpropagation
algorithm methods, namely Backpropagation and
Backpropagation using the Nguyen-Widrow method.
Backpropagation uses random initial weights while weights in
Nguyen-Widrow backpropagation use the Nguyen-Widrow
formula. The comparison results show that the accuracy in
Bacpropagation is 68.3168%, MSE 0.183, Training Time 0.25758
seconds, Precision 0.54455, Recall 1, and F1-Score 0.70513, while
in Bacpropagation on Nguyen-Widrow the accuracy is 66.6667%.
MSE 0.18327, Training Time 0.18736 seconds, Precision 0.54455,
Recall 1, and F1-Score 0.70513.