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PROVINCIAL SEGMENTATION IN INDONESIA: EXPLORING FACTORS INFLUENCING EDUCATION WITH SEM-PLS METHOD, INCORPORATING MODERATION EFFECTS AND FIMIX-PLS APPROACH

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 18 No. 3 (2024) · pp. 1955–1962

DOI
10.30598/barekengvol18iss3pp1955-1962
ISSN
2615-3017, 1978-7227
Published
2024-07-31
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The significance of education as a developmental metric is underscored by its designation as the 4th goal in the SDGs, which emphasizes ensuring inclusive, equitable, and high-quality education while also expanding lifelong learning opportunities for all. This research relies on two primary sources: secondary data from publications by the Indonesian Central Statistics Agency (BPS RI) in 2023 and the BPS website. The educational variables examined in this study are believed to be influenced by latent variables, including school performance, infrastructure, and poverty levels. Employing the Finite Mixture Partial Least Squares (FIMIX-PLS) approach, the research identified 13 valid and reliable indicators of educational variables. It delineated three regional groups based on the lowest BIC and CAIC values. In this structural equation research, the moderation effect is seen in the significance of the indirect relationship, especially the influence of Regional Poverty on Education with School Outcomes as a moderating construct.

Collaboration network of the authors

29 authors · 124 co-authorship links

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

  • Universitas Airlangga
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Dita AmeliaUniversitas Airlangga5
Sediono SedionoUniversitas Airlangga3
Muhammad Fariz Fadillah MardiantoUniversitas Airlangga2
Ni Wayan Widya Septia SariUniversitas Airlangga2
Anggara Teguh PrevianUniversitas Airlangga1
Zidni Ilmatun NurrohmahUniversitas Airlangga1
Toha SaifudinUniversitas Airlangga1
Mochammad Bayu FirmansyahUniversitas Airlangga1
Adnan Syawal Adilaha SadikinUniversitas Airlangga1
Aqil Azmi ReswaraUniversitas Airlangga1
Gabriella Agnes BudijonoUniversitas Airlangga1
Kimberly Maserati SiagianUniversitas Airlangga1
Adrian Wahyu AbdillahUniversitas Airlangga1
Idrus SyahzaqiUniversitas Airlangga1
Muhammad Rosyid Ridho Az ZuhroUniversitas Airlangga1
Dita AmeliaAffiliation unknown1
M. Fariz Fadillah MardiantoAffiliation unknown1
Elly AnaAffiliation unknown1
Aini Divayanti ArrofahAffiliation unknown1
Azzah Nazhifa Wina RamadhaniAffiliation unknown1
Aulia RamadhantiAffiliation unknown1
M. Nabil SaputraUniversitas Airlangga1
Aini Divayanti ArrofahUniversitas Airlangga1
Azzah Nazhifa Wina RamadhaniUniversitas Airlangga1
Aulia RamadhantiUniversitas Airlangga1

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 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">PROVINCIAL SEGMENTATION IN INDONESIA: EXPLORING FACTORS INFLUENCING EDUCATION WITH SEM-PLS METHOD, INCORPORATING MODERATION EFFECTS AND FIMIX-PLS APPROACH</dc:title>
	<dc:creator>Vanisa, Davina Shafa</dc:creator>
	<dc:creator>Rahmanita, Tentri Ryan</dc:creator>
	<dc:creator>Ana, Elly</dc:creator>
	<dc:creator>Kurniawan, Ardi</dc:creator>
	<dc:description xml:lang="en-US">The significance of education as a developmental metric is underscored by its designation as the 4th goal in the SDGs, which emphasizes ensuring inclusive, equitable, and high-quality education while also expanding lifelong learning opportunities for all. This research relies on two primary sources: secondary data from publications by the Indonesian Central Statistics Agency (BPS RI) in 2023 and the BPS website. The educational variables examined in this study are believed to be influenced by latent variables, including school performance, infrastructure, and poverty levels. Employing the Finite Mixture Partial Least Squares (FIMIX-PLS) approach, the research identified 13 valid and reliable indicators of educational variables. It delineated three regional groups based on the lowest BIC and CAIC values. In this structural equation research, the moderation effect is seen in the significance of the indirect relationship, especially the influence of Regional Poverty on Education with School Outcomes as a moderating construct.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2024-07-31</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/12710</dc:identifier>
	<dc:identifier>10.30598/barekengvol18iss3pp1955-1962</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application; 1955-1962</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol18iss3year2024</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12710/8545</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Davina Shafa Vanisa, Tentri Ryan Rahmanita, Elly Ana, Ardi Kurniawan</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>