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FUNCTION GROUP SELECTION OF SEMBUNG LEAVES (BLUMEA BALSAMIFERA) SIGNIFICANT TO ANTIOXIDANTS USING OVERLAPPING GROUP LASSO

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 16 No. 2 (2022) · pp. 721–728

DOI
10.30598/barekengvol16iss2pp721-728
ISSN
2615-3017, 1978-7227
Published
2022-06-01
Publisher
PATTIMURA UNIVERSITY
Language
eng

Abstract

Functional groups of sembung leaf metabolites can be detected using FTIR spectrometry by looking at the spectrum's shape from specific peaks that indicate the type of functional group of a compound. There were 35 observations and 1866 explanatory variables (wavelength) in this study. The number of explanatory variables more than the number of observations is high-dimensional data. One method that can be used to analyze high-dimensional data is penalized regression. The overlapping group lasso method is a development of the group-based penalized regression method that can solve the problem of selecting variable groups and members of overlapping groups of variables. The results of selecting the variable groups using the overlapping group lasso method found that the functional groups that were significant for the antioxidants of sembung leaves were C=C Unstructured, CN amide, Polyphenol, Sio2.

Collaboration network of the authors

40 authors · 101 co-authorship links · 3 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • IPB University
  • Bandung Islamic University
  • Universitas Halu Oleo
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Khairil Anwar NotodiputroBandung Islamic University10
Anwar FitriantoAffiliation unknown3
Anang KurniaAffiliation unknown2
Muh. SunanIPB University1
Unique Desyrre A. ResiloyIPB University1
Desy EndrianiIPB University1
Cici SuhaeniIPB University1
Gerry Alfa DitoIPB University1
Leni Anggraini SusantiIPB University1
Agus Mohamad SolehIPB University1
Dwi Agustin Nuriani SirodjAffiliation unknown1
Novi PuspitaAffiliation unknown1
Farit Mochamad AfendiAffiliation unknown1
Vera Maya SantiAffiliation unknown1
Indahwati IndahwatiAffiliation unknown1
Muhammad Edy RizalAffiliation unknown1
Aji H WigenaAffiliation unknown1
Hafizah IlmaAffiliation unknown1
Ni Gusti Ayu Putu Puteri SuantariAffiliation unknown1
Herlin FransiskaAffiliation unknown1
Winalia AgwilAffiliation unknown1
Eni MeylisahAffiliation unknown1
Dyah Setyo RiniAffiliation unknown1
Asrirawan AsrirawanAffiliation unknown1
Muhammad Azis SuprayogiAffiliation unknown1
I Made SumertajayaAffiliation unknown1
Agus Sofian Eka HidayatAffiliation unknown1
Dian KusumaningrumAffiliation unknown1
Arie PurwantoAffiliation unknown1
Nurul Fuady AdhaliaAffiliation unknown1
Abdul Khaliq ZulfattahAffiliation unknown1
Dodi Irawan SyaripAffiliation unknown1
Darwis DarwisUniversitas Halu Oleo1
Leny YulianiAffiliation unknown1
Ita WulandariAffiliation unknown1
Nur Fitriyani SahamonyAffiliation 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">FUNCTION GROUP SELECTION OF SEMBUNG LEAVES (BLUMEA BALSAMIFERA) SIGNIFICANT TO ANTIOXIDANTS USING OVERLAPPING GROUP LASSO</dc:title>
	<dc:creator>kusnaeni, kusnaeni</dc:creator>
	<dc:creator>Soleh, Agus M</dc:creator>
	<dc:creator>Afendi, Farit M</dc:creator>
	<dc:creator>Sartono, Bagus</dc:creator>
	<dc:description xml:lang="en-US">Functional groups of sembung leaf metabolites can be detected using FTIR spectrometry by looking at the spectrum's shape from specific peaks that indicate the type of functional group of a compound. There were 35 observations and 1866 explanatory variables (wavelength) in this study. The number of explanatory variables more than the number of observations is high-dimensional data. One method that can be used to analyze high-dimensional data is penalized regression. The overlapping group lasso method is a development of the group-based penalized regression method that can solve the problem of selecting variable groups and members of overlapping groups of variables. The results of selecting the variable groups using the overlapping group lasso method found that the functional groups that were significant for the antioxidants of sembung leaves were C=C Unstructured, CN amide, Polyphenol, Sio2.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2022-06-01</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/5461</dc:identifier>
	<dc:identifier>10.30598/barekengvol16iss2pp721-728</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan; 721-728</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol16iss2year2022</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/5461/4500</dc:relation>
</oai_dc:dc>