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ROBUST LEAST MEDIAN OF SQUARE MODELLING USING SEEMINGLY UNRELATED REGRESSION WITH GENERALIZED LEAST SQUARE ON PANEL DATA FOR TUBERCULOSIS CASES

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 18 No. 4 (2024) · pp. 2293–2306

DOI
10.30598/barekengvol18iss4pp2293-2306
ISSN
2615-3017, 1978-7227
Published
2024-10-11
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Tuberculosis, primarily affecting the lungs and other organs, was the leading cause of death worldwide before the COVID-19 pandemic and continues to be a significant health concern. This research examined tuberculosis (TB) using a panel dataset. As a consequence, the datasets may contain outliers and contemporaneous correlations. A Robust Least Median of Square (LMS) model was developed in this research by combining Seemingly Unrelated Regression (SUR) with Generalized Least Square (GLS) on panel data to provide an analysis overview to overcome outliers and contemporaneous correlations. Based on secondary data obtained from the Central Bureau of Statistics of the Gorontalo Province and the Ministry of Health of the Gorontalo Province, this research examines TB cases between 2017 and 2021. The Chow test result suggests that CEM is the most appropriate model for analyzing panel data for TB cases in Gorontalo Province between 2017 and 2021. Due to the presence of outliers and influential observations in the data, robust LMS is employed. Furthermore, there is a problem of contemporaneous correlation in this research. Each regency or city can mitigate this problem by implementing robust LMS using SUR with GLS.

Collaboration network of the authors

39 authors · 124 co-authorship links · 30 across different organisations

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

  • State University of Gorontalo
  • University of Brawijaya
  • Universitas Islam Negeri Imam Bonjol Padang
  • Universitas Halu Oleo
  • Sultan Ageng Tirtayasa University
  • Sunan Kalijaga State Islamic University Yogyakarta
  • Universitas Pamulang
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Lailany YahyaState University of Gorontalo7
Agusyarif Rezka NuhaState University of Gorontalo6
Hasan S. PanigoroState University of Gorontalo4
Emli RahmiState University of Gorontalo4
İsnani DartiUniversity of Brawijaya2
Novianita AchmadState University of Gorontalo2
Ismail DjakariaState University of Gorontalo2
Muhammad Rezky Friesta PayuState University of Gorontalo2
Sri Indriani LadjaliState University of Gorontalo2
Herlina JusufState University of Gorontalo2
Sri Adiningsi B. UsmanState University of Gorontalo1
Nurwan NurwanState University of Gorontalo1
Moh Rizal HusainState University of Gorontalo1
Isran R OliiState University of Gorontalo1
Nur Safitri AbdulState University of Gorontalo1
Gusti Arviana RahmanUniversitas Halu Oleo1
Syarif AbdullahSultan Ageng Tirtayasa University1
Sri Istiyarti Uswatun ChasanahSunan Kalijaga State Islamic University Yogyakarta1
Nina ValentikaUniversitas Pamulang1
La Ode SabranUniversitas Islam Negeri Imam Bonjol Padang1
Ilham Dangu RianjayaUniversitas Dharma Andalas1
Lilis Harianti HasibuanUniversitas Islam Negeri Imam Bonjol Padang1
Sri Lestari MahmudState University of Gorontalo1
Nazrilla Hasan LaitaState University of Gorontalo1
Agus SuryantoUniversity of Brawijaya1
Nurhalis HasanState University of Gorontalo1
Rusniwati S. ImranState University of Gorontalo1
Zulfatra LamudaState University of Gorontalo1
Amelia Tri Rahma SidikAffiliation unknown1
Revandi S. PakayaAffiliation unknown1
Rusdianto IbrahimAffiliation unknown1
Siti MaisarohAffiliation unknown1
Agus SuryantoState University of Semarang1

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">ROBUST LEAST MEDIAN OF SQUARE MODELLING USING SEEMINGLY UNRELATED REGRESSION WITH GENERALIZED LEAST SQUARE ON PANEL DATA FOR TUBERCULOSIS CASES</dc:title>
	<dc:creator>Adityaningrum, Amanda</dc:creator>
	<dc:creator>Resmawan, Resmawan</dc:creator>
	<dc:creator>Brahim, Annisa Maharani</dc:creator>
	<dc:creator>Isa, Dewi Rahmawaty</dc:creator>
	<dc:creator>Nashar, La Ode</dc:creator>
	<dc:creator>Asriadi, Asriadi</dc:creator>
	<dc:description xml:lang="en-US">Tuberculosis, primarily affecting the lungs and other organs, was the leading cause of death worldwide before the COVID-19 pandemic and continues to be a significant health concern. This research examined tuberculosis (TB) using a panel dataset. As a consequence, the datasets may contain outliers and contemporaneous correlations. A Robust Least Median of Square (LMS) model was developed in this research by combining Seemingly Unrelated Regression (SUR) with Generalized Least Square (GLS) on panel data to provide an analysis overview to overcome outliers and contemporaneous correlations. Based on secondary data obtained from the Central Bureau of Statistics of the Gorontalo Province and the Ministry of Health of the Gorontalo Province, this research examines TB cases between 2017 and 2021. The Chow test result suggests that CEM is the most appropriate model for analyzing panel data for TB cases in Gorontalo Province between 2017 and 2021. Due to the presence of outliers and influential observations in the data, robust LMS is employed. Furthermore, there is a problem of contemporaneous correlation in this research. Each regency or city can mitigate this problem by implementing robust LMS using SUR with GLS.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2024-10-11</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12517</dc:identifier>
	<dc:identifier>10.30598/barekengvol18iss4pp2293-2306</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application; 2293-2306</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol18iss4year2024</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12517/8898</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Amanda Adityaningrum, Resmawan Resmawan, Annisa Maharani Brahim, Dewi Rahmawaty Isa, La Ode Nashar, Asriadi Asriadi</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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