KLASIFIKASI PENYAKIT KARDIOVASKULAR MENGGUNAKAN ALGORITMA RANDOM FOREST, SUPPORT VECTOR MACHINE, DAN DECISION TREE
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Abstract
Cardiovascular disease is a disease caused by narrowing or blockage of blood vessels. This disease is caused by a malfunction of the heart and blood vessels, which can cause death. According to WHO, there are 18 million deaths caused by cardiovascular disease. This research aims to carry out a classification to predict Cardiovascular Disease because this disease tends to be difficult to cure. The classification model used to predict cardiovascular disease is the Random Forest Algorithm, Support Vector Machine Algorithm, and Decision Tree Algorithm. The dataset used is 70.000 with 13 variables, namely id, age, height, weight, gender, systolic blood pressure, diastolic blood pressure, cholesterol, glucose, smoking, alcohol intake, physical activity, and cardio (presence or absence of Cardiovascular Disease). The Support Vector Machine algorithm is an algorithm that has the highest evaluation value among the three algorithms used, namely with an average Accuracy of 72%, Precision of 72%, Recall of 72%, and F1-Score of 72%. Meanwhile, the Decision Tree Algorithm is an algorithm that has the lowest evaluation value among the three algorithms used, namely with an average Accuracy of 70%, Precision of 70%, Recall of 70%, and F1-Score of 69%.
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