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CLASSIFICATION OF PNEUMONIA DISEASE USING THE MINI XCEPTION MODEL ON X-RAY DATA

Jurnal Ilmu Pendidikan Indonesia · Vol. 14 No. 2 (2026) · pp. 97–104

DOI
10.31957/jipi.v14i2.5602
ISSN
2623-226X, 2338-3402
Published
2026-06-04
Publisher
Master of Science Education Program, Postgraduate Program of Cenderawasih University
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Pneumonia is a disease that often causes death in Indonesia. In general, many that cause a person to develop pneumonia include pneumonia due to bacterial, viral, mycoplasma pneumonia, fungal pneumonia. There are many ways to detect a patient grouped into one type of pneumonia. One way is to use an X-ray machine. X-ray is technology that can send waves of electromagnetic radiation briefly to scan the condition of the inside of the body. In this study, we tried to classify patients affected by bacterial pneumonia and viral pneumonia as well as normal people. The data we use is a picture of the lungs taken from the X-ray results. This research was conducted by applying the mini Xception model using the python program. The model can predict the results of X-ray scans that belong to the class of bacterial pneumonia very well, as seen from the value of precision and sensitivity of 80 and 97 percent, respectively. Viral pneumonia class can not be predicted as good as the two previous classes, but the results obtained are quite good as seen from the value of precision and sensitivity of 85 and 67 percent, respectively. The overall accuracy of the model obtained is 0.86.

Collaboration network of the authors

8 authors · 20 co-authorship links

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Co-authorOrganisationJoint articles
TommiAffiliation unknown2
Irja Tobawan SimbiakAffiliation unknown2
Inriyanti Sri Pertiwi GintingAffiliation unknown2
Anggraeni Permata SariAffiliation unknown2

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://ejournal.uncen.ac.id/index.php/JIPI/oai, first harvested 1 Nov 2026, last seen 1 Nov 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en-US">CLASSIFICATION OF PNEUMONIA DISEASE USING THE MINI XCEPTION MODEL  ON X-RAY DATA</dc:title>
	<dc:creator>Siregar, Anggrainy Togi Marito</dc:creator>
	<dc:creator>Fitri, Dina Jumiatul</dc:creator>
	<dc:creator>Haay, Happy Alyzhya</dc:creator>
	<dc:creator>Samosir, Rasi Kasim</dc:creator>
	<dc:description xml:lang="en-US">Pneumonia is a disease that often causes death in Indonesia. In general, many that cause a person to develop pneumonia include pneumonia due to bacterial, viral, mycoplasma pneumonia, fungal pneumonia. There are many ways to detect a patient grouped into one type of pneumonia. One way is to use an X-ray machine. X-ray is technology that can send waves of electromagnetic radiation briefly to scan the condition of the inside of the body. In this study, we tried to classify patients affected by bacterial pneumonia and viral pneumonia as well as normal people. The data we use is a picture of the lungs taken from the X-ray results. This research was conducted by applying the mini Xception model using the python program. The model can predict the results of X-ray scans that belong to the class of bacterial pneumonia very well, as seen from the value of precision and sensitivity of 80 and 97 percent, respectively. Viral pneumonia class can not be predicted as good as the two previous classes, but the results obtained are quite good as seen from the value of precision and sensitivity of 85 and 67 percent, respectively. The overall accuracy of the model obtained is 0.86.</dc:description>
	<dc:publisher xml:lang="en-US">Master of Science Education Program, Postgraduate Program of Cenderawasih University</dc:publisher>
	<dc:date>2026-06-04</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ejournal.uncen.ac.id/index.php/JIPI/article/view/5602</dc:identifier>
	<dc:identifier>10.31957/jipi.v14i2.5602</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Pendidikan Indonesia; Vol. 14 No. 2 (2026): JURNAL ILMU PENDIDIKAN INDONESIA; 97-104</dc:source>
	<dc:source xml:lang="id-ID">Jurnal Ilmu Pendidikan Indonesia; Vol 14 No 2 (2026): JURNAL ILMU PENDIDIKAN INDONESIA; 97-104</dc:source>
	<dc:source>2623-226X</dc:source>
	<dc:source>2338-3402</dc:source>
	<dc:source>10.31957/jipi.v14i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ejournal.uncen.ac.id/index.php/JIPI/article/view/5602/3707</dc:relation>
	<dc:rights xml:lang="en-US">https://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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