Open AccessPeningkatan Akurasi Klasifikasi Backpropagation Menggunakan Artificial Bee Colony dan K-NN Pada Penyakit Jantung
Author(s) -
Pandito Dewa Putra,
Sukemi Sukemi,
Dian Palupi Rini
Publication year - 2021
Publication title -
jurnal media informatika budidarma/jurnal media informatika budidarma
Language(s) - English
Resource type - Journals
eISSN - 2614-5278
pISSN - 2548-8368
DOI - 10.30865/mib.v5i1.2634
Subject(s) - backpropagation , artificial intelligence , heart disease , classifier (uml) , medicine , computer science , artificial neural network
Heart disease has ranked as the leading cause of death in the world, accounting for around 17.3 million deaths per year with some causes, as high blood pressure, diabetes, cholesterol fluctuation, fatigue, and some others which is collected on dataset. Heart disease dataset that was applied is cleveland heart disease with fourteen (14) data atribute. The method that was applied in this research was using Backpropagation algorithm on heart disease classifying, where will be combined Artificial Bee Colony and k-Nearest Neighbor algorithm for features or atribute choose due to this technique can increase classifier model accuracy which is produced as much as 94,23%.