Article Per Year (5 Year)
p-Index From 2019 - 2024
0
P-Index
This Author published in this journals
All Journal Indonesian Journal of Artificial Intelligence and Data Mining
Boni Iqbal
Unknown Affiliation
Computer Science & IT

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

Found 1 Documents
Search

 1 
Implementation of Backpropagation Neural Network to Detect Suspected Lung Disease Fadhilah Syafria; Boni Iqbal; Elvia Budianita; Iis Afrianty
Indonesian Journal of Artificial Intelligence and Data Mining Vol 1, No 1 (2018): March 2018
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (519.707 KB) | DOI: 10.24014/ijaidm.v1i1.5023

Abstract

Many People were less concerned with lung health, it caused people identified as suffering from lung diseases. Early symptoms that often appear  was cough that took a long time and could be the beginning of more severe disease. Therefore it was necessary to create application that could detect suspected person contracted lung disease. The applications were made by using artificial neural network with Backpropagation with initial input data, symptoms by patients of lung diseases. The symptoms were 22, and kind of lung diseases as a diagnosis were asthma, pneumonia, pulmonary tuberculosis and lung cancer. It used medical records of lung disease as much as 110 data. Network training uses 3 different architectures [input neurons ; hidden neurons ; output neurons], liked [22; 22 ; 2], [22 ; 33 ; 2] and [22 ; 43 ; 2]. Testing with 2 training data sharing and test data, namely comparison 90:10 and 80:20. The Parameters values were used namely learning rate 0.1, 0.3, 0.5, 0.7 and 0.9. The number of epoch was used, that is 15 epoch, 25 epoch and 35 epoch. Based on the tests performed, it was obtained an accuracy system on the 90:10 data comparison of 82% and the 80:20 data ratio of 82% as well. Thus, backpropagation method could be applied in detecting suspected lung diseases.
Co-Authors Elvia Budianita Fadhilah Syafria Iis Afrianty