Fathurrahman, Haris Imam Karim and Puriyanto, Riky Dwi and Kamilah, Farhah and Azhari, Ahmad (2022) Rapid Test of Pneumonia Cells: An Alternative Simple Application. Journal of Electrical and Electronics Engineering, 15 (2). pp. 110-117.
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Abstract
In this pandemic period, pneumonia is often
found in various cases. In many cases, COVID-19 has
an adverse effect on people with pneumonia. Early
detection of pneumonia can help health institutions
map pneumonia in the community. However,
pneumonia detection still uses conventional methods
and takes a long time. This study detects pneumonia
bacteria consisting of Acinetobacter baumannii and
Pseudomonas aeruginosa. This study uses the DIBaS
database, which consists of several bacterial images.
This database is used to compare two classes, namely
pneumonia and non-pneumonia. Detection is carried
out using an artificial intelligence approach using the
DenseNet121 and DenseNet169 methods. This study
also uses the Genetic Algorithm optimization method to
increase the accuracy of detecting pneumonia bacterial
cells. The Genetic Algorithm provides random values
for the last two DenseNet121 and DenseNet169
training layers. As a result, the accuracy of the
DenseNet121 and DenseNet169 methods reached 95%
and 96.7%, respectively. The optimization method
intervention gave an increase of 5.2% and 3.4% over
the original method, respectively. The best model
results from this method are used as a reference model
in making applications for the rapid detection of
pneumonia with an average speed of accuracy
reaching 4.25s. This computer-based application
provides promising results for the future to be applied
to the broader community.
Item Type: | Artikel Umum |
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Subjects: | R Medicine > RZ Other systems of medicine T Technology > T Technology (General) |
Divisi / Prodi: | Faculty of Industrial Technology (Fakultas Teknologi Industri) > S1-Electrical Engineering (S1-Teknik Elektro) |
Depositing User: | Haris Imam Karim Fathurrahman |
Date Deposited: | 20 Jan 2023 04:06 |
Last Modified: | 20 Jan 2023 04:06 |
URI: | http://eprints.uad.ac.id/id/eprint/39007 |
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