Aplikasi K-Nearest Neighbor (KNN) untuk Klasifikasi Penyakit Kardiovaskuler
Keywords:
data mining, machine learning, klasifikasi, kardiovaskuler, K-Nearest NeighborAbstract
Data mining dan machine learning adalah dua alat
yang memainkan peran penting dalam studi analisis data dan
sistem keputusan. Klasifikasi adalah fungsi dari data mining.
Dalam fungsi klasifikasi, pengurutan atau pemetaan terjadi
berdasarkan kedekatan atau kesamaan atribut data dengan label
yang ditentukan. Algoritma K-Nearest Neighbor (KNN) adalah
metode non-parametrik yang digunakan untuk klasifikasi dan
regresi. Model prediksi penyakit kardiovaskular dengan
algoritma KNN digunakan untuk mengidentifikasi dan
memprediksi penyakit kardiovaskular. Algoritma KNN
menggunakan jarak Euclidian untuk proses prediksi data latih.
Dataset yang digunakan adalah 400 dengan 7 atribut yaitu
umur, jenis kelamin, tekanan darah sistolik, kolesterol, talach,
oldpeak dan slope. Hasil implementasi algoritma KNN
menghasilkan performansi dengan akurasi sebesar 75,75%.
Nilai presisinya adalah 76,78%, sedangkan recall menghasilkan
77,14%.
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