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MULTILEVEL REGRESSIONS FOR MODELING MEAN SCORES OF NATIONAL EXAMINATIONS

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 18 No. 1 (2024) · pp. 0323–0332

DOI
10.30598/barekengvol18iss1pp0323-0332
ISSN
2615-3017, 1978-7227
Published
2024-03-01
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

National Exam known as UN score is the final evaluation to determine the achievement of national graduate competency standards in the school. The determinants of the achievement of the standards can’t be separated from the role of schools and local governments in which this regard is known as nested. In the field of statistics, this phenomenon can be described with a multilevel model, where level-1 is the school while level-2 is the district where the school is located. Several multilevel models are used to describe the phenomenon, the result shows that the two-level regression model without interaction is selected as the best model and the variables which affect the UN average scores significantly at level-1 are school status, the ratio between laboratories and students, while the variable at level-2 is expenditure per capita of district/city. From this study, that educational institutions' steps in achieving a graduation standard can be right on the target.

Collaboration network of the authors

29 authors · 65 co-authorship links

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

  • IPB University
  • Bandung Islamic University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Anang KurniaAffiliation unknown5
Hari WijayantoAffiliation unknown2
Ade RiyawanAffiliation unknown2
Wa Ode Rona FreyaAffiliation unknown1
Kusman SadikAffiliation unknown1
Abdullah PannuAffiliation unknown1
Utami Dyah SyafitriAffiliation unknown1
Ratna Nur Mustika SanusiAffiliation unknown1
Anik DjuraidahAffiliation unknown1
Ismail PranataAffiliation unknown1
Erfiani ErfianiAffiliation unknown1
Yesan TiaraAffiliation unknown1
Rika RachmawatiAffiliation unknown1
Asep SaefuddinIPB University1
Satria June AdwendiAffiliation unknown1
Khairil Anwar NotodiputroBandung Islamic University1
Andika Putri RatnasariAffiliation unknown1
Zetil HikmahAffiliation unknown1
Irvanal HaqAffiliation unknown1
Efriwati EfriwatiAffiliation unknown1
Wa Ode Rahmalia SafitriAffiliation unknown1
Farit Mochamad AfendiAffiliation unknown1
Assyifa Lala Pratiwi HamidAffiliation unknown1
Aji Hamim WigenaAffiliation unknown1
Alona DwinataAffiliation 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) 
<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">MULTILEVEL REGRESSIONS FOR MODELING MEAN SCORES OF NATIONAL EXAMINATIONS</dc:title>
	<dc:creator>Nurfadilah, Khalilah</dc:creator>
	<dc:creator>Aidi, Muhammad Nur</dc:creator>
	<dc:creator>Notodiputro, Khairil A.</dc:creator>
	<dc:creator>Susetyo, Budi</dc:creator>
	<dc:description xml:lang="en-US">National Exam known as UN score is the final evaluation to determine the achievement of national graduate competency standards in the school. The determinants of the achievement of the standards can’t be separated from the role of schools and local governments in which this regard is known as nested. In the field of statistics, this phenomenon can be described with a multilevel model, where level-1 is the school while level-2 is the district where the school is located. Several multilevel models are used to describe the phenomenon, the result shows that the two-level regression model without interaction is selected as the best model and the variables which affect the UN average scores significantly at level-1 are school status , the ratio between laboratories and students , while the variable at level-2 is expenditure per capita of district/city . From this study, that educational institutions' steps in achieving a graduation standard can be right on the target.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2024-03-01</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/10354</dc:identifier>
	<dc:identifier>10.30598/barekengvol18iss1pp0323-0332</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application; 0323-0332</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol18iss1year2024</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/10354/7592</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Khalilah Nurfadilah, Muhammad Nur Aidi, Khairil A. Notodiputro, Budi Susetyo</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>