Gejala penyakit kardiovaskular juga sulit untuk diidentifikasi. Berbagai faktor seperti usia, kadar kolesterol, dan gaya hidup tidak sehat dapat memicu penyakit kardiovaskular. Tidak dapat dipungkiri bahwa penyakit kardiovaskular adalah penyebab kematian nomor satu di dunia.
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With this research, it is expected to be able to increase readers' knowledge and insight related to how to analyze cardiovascular disease using logistic regression algorithms and the main factors that cause cardiovascular disease. In predicting cardiovascular disease, a logistic regression algorithm will be used to see the interrelation between the dependent variable and the independent variables involved. The research area used is the area of analysis data where the analyzed data are on factors that influence the presence of cardiovascular disease in the State of Cleveland. In this study, a dataset consisting of 14 attributes with class labels was used as the basis for identification as a link between factors that cause cardiovascular disease. This study was conducted to predict the main factors causing cardiovascular disease. It takes careful understanding and analysis related to patient medical record data and identification of the parameters that cause this disease. The symptoms of cardiovascular disease are also challenging to identify. Various factors such as age, cholesterol level, and unhealthy lifestyle can trigger cardiovascular disease. It is undeniable that cardiovascular disease is the number one cause of death in the world. Model Prediksi Regresi Logistik untuk Penyakit Kardiovaskular
Logistic Regression Prediction Model for Cardiovascular Disease Logistic Regression Prediction Model for Cardiovascular Disease International Journal of New Media Technology View Publication Info
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