Indonesian Journal of Artificial Intelligence and Data Mining
Vol 1, No 1 (2018): March 2018

Implementation of Backpropagation Neural Network to Detect Suspected Lung Disease

Fadhilah Syafria (UIN Sultan Syarif Kasim Riau)
Boni Iqbal (Unknown)
Elvia Budianita (Unknown)
Iis Afrianty (Unknown)



Article Info

Publish Date
01 Mar 2018

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.

Copyrights © 2018






Journal Info

Abbrev

IJAIDM

Publisher

Subject

Computer Science & IT

Description

Indonesian Journal of Artificial Intelligence and Data Mining (IJAIDM) is an electronic periodical publication published by Puzzle Research Data Technology (Predatech) Faculty of Science and Technology UIN Sultan Syarif Kasim Riau, Indonesia. IJAIDM provides online media to publish scientific ...