JURNAL MEDIA INFORMATIKA BUDIDARMA
Vol 5, No 1 (2021): Januari 2021

Peningkatan Akurasi Klasifikasi Backpropagation Menggunakan Artificial Bee Colony dan K-NN Pada Penyakit Jantung

Pandito Dewa Putra (Universitas Sriwijaya, Palembang)
Sukemi Sukemi (Universitas Sriwijaya, Palembang)
Dian Palupi Rini (Universitas Sriwijaya, Palembang)

Article Info

Publish Date
22 Jan 2021

Abstract

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%.

Copyrights © 2021




Citation Download
RIS
EndNote, Reference Manager, ProCite
BibTex
Latex, Jabref
Original Source
Download Original
Google Scholar
Check in Google Scholar
Journal Info
JURNAL MEDIA INFORMATIKA BUDIDARMA
Website

Abbrev

mib

Publisher

Sekolah Tinggi Manajemen Informatika dan Komputer Budi Darma

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Description

Decission Support System, Expert System, Informatics tecnique, Information System, Cryptography, Networking, Security, Computer Science, Image Processing, Artificial Inteligence, Steganography etc (related to informatics and computer ...