Klasifikasi Penyakit Jantung Menggunakan Algoritma ANN dengan Persentase diatas 70%
DOI:
https://doi.org/10.59581/jkts-widyakarya.v2i3.3922Keywords:
Artificial Neural Network, Heart Disease Classification, Performance AnalysisAbstract
Heart disease is one of the biggest causes of death in the world. This research examines the use of the Artificial Neural Network (ANN) algorithm to classify heart disease based on 303 medical data of heart disease patients obtained from the Kaggle dataset center. The data used includes medical parameters such as age, gender, blood pressure, cholesterol levels and other examination results. Various ANN architectures were tested to find the optimal configuration in terms of the number of hidden layers and neurons in each layer. Model performance is evaluated using metrics such as accuracy, precision, recall, and F1-score. From the results of the performance measurement research, an accuracy rate of 97.06%, precision of 92.30%, recall of 92.30%, and F1-Score of 92.30% were obtained.
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