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All Journal OKTAL : Jurnal Ilmu Komputer dan Sains
EvaEva Fauziah
Universitas Pamulang
Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Social Sciences

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Penerapan Metode Decision Tree Menggunakan Algoritma Iterative Dichotomiser 3 (ID3) Untuk Klasifikasi Resiko Penyakit Jantung EvaEva Fauziah; Ahmad Fikri Zulfikar
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 2 No 04 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

Heart or cardiovascular disease is a condition caused by narrowing and blockage of blood vessels, which is one of the most common deadly diseases in every country. The risk of heart disease becomes an event that cannot be avoided because of a lack of attention to heart health where a healthy lifestyle and healthy eating patterns are not implemented. For this reason, an analysis of the risk of heart disease is needed. Classification is a data mining method that is widely used in determining a predictable decision based on previous data that is processed using a classification algorithm. The classification algorithm used is iterative dichotomizer 3 (ID3) using a dataset taken from the UCI Machine Learning Repository, sourced from V.A. Medical Center, Long Beach and Cleveland Clinic Foundation. The dataset consists of 14 attributes including: age, sex, cp, tresbps, chol, fbs, restecg, thalach, exang, oldpeak, slope, ca, thal, num (predictive attribute). The evaluation method used is the confusion matrix with the results of calculating an accuracy of 85.71%, a precision of 84.62% and a recal of 84.62%.
Co-Authors Ahmad Fikri Zulfikar