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Open access Jurnal SINTA 3

CLASSIFICATION OF STUNTING IN CHILDREN UNDER FIVE YEARS IN PADANG CITY USING SUPPORT VECTOR MACHINE

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 16 No. 3 (2022) · pp. 771–778

DOI
10.30598/barekengvol16iss3pp771-778
ISSN
2615-3017, 1978-7227
Published
2022-09-01
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Stunting is a nutritional problem in children characterized by the child’s height that is less than twice the standard deviation of the median standard from children growth that has been determined by the WHO. Stunting is influenced by many factors. If the conditional of these factors are known, it can be expected earlier whether a child is stunted or not. In this study, the prediction of stunting was carried out using the Support Vector Machine (SVM) classification method. SVM is a method to find the best hyperplane that can be used to separate two or more classes. In this study, the parameter of the SVM model that must be determined is the cost value and gamma. Based on the result of research using parameters cost=10 and gamma=5, the estimation result of the classification with 100% accuracy can be obtained.

Collaboration network of the authors

12 authors · 26 co-authorship links

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  • Andalas University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Mahdhivan SyafwanAndalas University4
Yana WulandariAffiliation unknown2
Riswan EfendiAffiliation unknown2
Nor Azah SamatAffiliation unknown2
Dodi DeviantoAffiliation unknown1
Ferra YanuarAffiliation unknown1
Maiyastri MaiyastriAffiliation unknown1
Latifah ZahraAffiliation unknown1

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://ojs3.unpatti.ac.id/index.php/barekeng/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">CLASSIFICATION OF STUNTING IN CHILDREN UNDER FIVE YEARS IN PADANG CITY USING SUPPORT VECTOR MACHINE</dc:title>
	<dc:creator>Rahmi, Izzati</dc:creator>
	<dc:creator>Susanti, Mega</dc:creator>
	<dc:creator>Yozza, Hazmira</dc:creator>
	<dc:creator>Wulandari, Frilianda</dc:creator>
	<dc:description xml:lang="en-US">Stunting is a nutritional problem in children characterized by the child’s height that is less than twice the standard deviation of the median standard from children growth that has been determined by the WHO. Stunting is influenced by many factors. If the conditional of these factors are known, it can be expected earlier whether a child is stunted or not. In this study, the prediction of stunting was carried out using the Support Vector Machine (SVM) classification method. SVM is a method to find the best hyperplane that can be used to separate two or more classes. In this study, the parameter of the SVM model that must be determined is the cost value and gamma. Based on the result of research using parameters cost=10 and gamma=5, the estimation result of the classification with 100% accuracy can be obtained.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2022-09-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/5271</dc:identifier>
	<dc:identifier>10.30598/barekengvol16iss3pp771-778</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications; 771-778</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol16iss3year2022</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/5271/4595</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2022 Izzati Rahmi, Mega Susanti, Hazmira Yozza, Frilianda Wulandari</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>