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Hepatitis classification using support vector machines and random forest

IAES International Journal of Artificial Intelligence · Vol. 10 No. 2 (2021) · hlm. 446–451

DOI
10.11591/ijai.v10.i2.pp446-451
ISSN
2252-8938, 2089-4872
Terbit
2021-06-01
Penerbit
Institute of Advanced Engineering and Science
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Hepatitis is a medical condition defined by inflammation of the liver. It can be caused by infection of the liver by hepatitis viruses or is of unknown aetiology. There are 5 main hepatitis viruses, such as virus types A, B, C, D and E. The infection may occur with limited or no symptoms, but also may include some symptoms like abdominal pain, dark urine, extreme fatigue, jaundice, nausea or vomiting. Because Indonesia is a large archipelago, the prevalence of viral infections varies greatly by region of acute hepatitis patients. This research uses data of hepatitis examination result with amount of 113 data and 5 features. The method that used is support vector machines (SVM) and random forest method. SVM is the classification method that uses discriminant hyper-plane, dividing to classes. meanwhile, random forest is a tree-based ensemble depending on a collection of random variables. SVM and random forest (RF) are applied to predict hepatitis data, and then the results will be compared.

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Sumber metadata: OAI-PMH (metadata jurnal) http://ijai.iaescore.com/index.php/IJAI/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">Hepatitis classification using support vector machines and random forest</dc:title>
	<dc:creator>Aurelia, Jane Eva</dc:creator>
	<dc:creator>Rustam, Zuherman</dc:creator>
	<dc:creator>Wirasati, Ilsya</dc:creator>
	<dc:creator>Hartini, Sri</dc:creator>
	<dc:creator>Saragih, Glori Stephani</dc:creator>
	<dc:subject xml:lang="en-US"></dc:subject>
	<dc:subject xml:lang="en-US">Classification; Hepatitis; Machine learning; Random forest; Support vector machines</dc:subject>
	<dc:description xml:lang="en-US">Hepatitis is a medical condition defined by inflammation of the liver. It can be caused by infection of the liver by hepatitis viruses or is of unknown aetiology. There are 5 main hepatitis viruses, such as virus types A, B, C, D and E. The infection may occur with limited or no symptoms, but also may include some symptoms like abdominal pain, dark urine, extreme fatigue, jaundice, nausea or vomiting. Because Indonesia is a large archipelago, the prevalence of viral infections varies greatly by region of acute hepatitis patients. This research uses data of hepatitis examination result with amount of 113 data and 5 features. The method that used is support vector machines (SVM) and random forest method. SVM is the classification method that uses discriminant hyper-plane, dividing to classes. meanwhile, random forest is a tree-based ensemble depending on a collection of random variables. SVM and random forest (RF) are applied to predict hepatitis data, and then the results will be compared.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2021-06-01</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"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijai.iaescore.com/index.php/IJAI/article/view/20852</dc:identifier>
	<dc:identifier>10.11591/ijai.v10.i2.pp446-451</dc:identifier>
	<dc:source xml:lang="en-US">IAES International Journal of Artificial Intelligence (IJ-AI); Vol 10, No 2: June 2021; 446-451</dc:source>
	<dc:source>2252-8938</dc:source>
	<dc:source>2089-4872</dc:source>
	<dc:source>10.11591/ijai.v10.i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/view/20852/13126</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2021 Institute of Advanced Engineering and Science</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>