Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Mohammad Setya Adi Fauzi
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Perbandingan Jaringan Saraf Tiruan LVQ Dengan Backpropagation Dalam Deteksi Dini Penyakit Jantung Koroner Mohammad Setya Adi Fauzi; Bayu Rahayudi; Candra Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1191.652 KB)

Abstract

Coronary heart disease is one of the highest causes of death in the world. The World Heart Federation estimates the number of deaths from this disease in Southeast Asia to reach 1.8 million cases in 2014. In Indonesia in 2013 recorded 883,447 people diagnosed with coronary heart disease with the majority of patients aged 55-64 years and the death rate due to this disease is enough high, ie 45% of all deaths in Indonesia, so early detection of coronary heart disease is very important for the risk of this disease can be minimized. One of the popular machine learning techniques and fits in this case is the artificial neural network. Artificial neural networks are systems that are inspired by reasoning processes in human neural networks. In this study the authors compared the performance of artificial neural network LVQ method and Backpropagation method for early detection of coronary heart disease. The variables of coronary heart disease used in this study were gender, age, pulse, systolic blood pressure, cholesterol, blood sugar, triglycerides, chest pain, shortness of breath, and cough. From the results of this study showed that the Backpropagation method is better than the LVQ method with the comparison of the accuracy value of training of 95,99097% for Backpropagation compared to 66,89659% for LVQ and the accuracy value of testing of 68,76034% for Backpropagation compared to 54,30313% for LVQ.
Co-Authors Bayu Rahayudi Candra Dewi