Algoritma Backpropagation Metode Levenberg Marquardt Dalam Memprediksi Penyakit Stroke
DOI:
https://doi.org/10.47065/bulletincsr.v3i2.229Keywords:
Backpropagation; Levenberg-Marquardt; Stroke; Prediction; Neural NetworkAbstract
In Southeast Asia, stroke is the third leading cause of disability and the disease with the second highest risk of death. A stroke occurs when a blood vessel in the brain is blocked or bursts, preventing some cells or brain tissue from receiving the oxygen they need from the blood supply. This study focuses on predicting stroke using the Levenberg Marquardt algorithm. Stroke prediction data is taken from the Kaggle website which consists of 5110 records. The attributes used to predict stroke consist of 10 attributes, namely gender, age, patient hypertension, heart disease, marital status, type of work, type of residence, average glucose level, body weight, and smoking status. The results of this study are the prediction of stroke by training and testing MSE = 0.0550 at Epoch = 10000 with 10-10-1 architecture.
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