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A COMPARISON OF M-ESTIMATION AND S-ESTIMATION ON THE FACTORS AFFECTING IR DHF IN EAST JAVA IN 2017

The Indonesian Journal of Public Health · Vol. 16 No. 3 (2021) · hlm. 349–362

DOI
10.20473/ijph.v16i3.2021.349-362
ISSN
2540-8836, 1829-7005
Terbit
2021-11-30
Penerbit
Universitas Airlangga
Bahasa
eng

Abstrak

ABSTRACTRobust regression on M estimation and S estimation is the Ordinary Least Square (OLS) regression on the data outlier. East Java is one of the provinces in Indonesia with a high case fatalitiy rate (1.34%). The raising of Dengue Haemoragic Fever (DHF) in East Java has been influenced by climate, population density, human behavior, and environmental sanitation. This study aimed to compare robust regression research by using M estimation and S estimation on the factors that affect IR DHF. This was done to get the best model regression on the data outlier based on the biggest R2 adjusted and the smallest MSE. This study utitlized observational research with a non-reactive research design using secondary data. The independent variable consisted of population density, healthy behavior, healthy living environment house, and precipitation in East Java in 2017. The dependent variable was incident rate of DHF in 2017. The population included 38 regencies in East Java, while the sample was 35 regencies/cities selected using simple random sampling. The analysis used robust regression on M estimation and S estimation weighting by Tukey's Bisquare. Robust regression on S estimation was found to be the best robust regression on data outlier with R2 adjusted (0.996) and MSE (0.229). Robust regression on S estimation was = 54.826 + 0.011 (population density) – 0.136 (% healthy behavior) - 0,404 (% healthy house ) - 0,005 (precipitation).Some factors that affect IR DHF can be the main focus for the prevention and control of DHF for the government and society. Keywords: robust regression, outlier, estimation, estimation, DHF

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  • Diponegoro University
  • Universitas Raharja
  • Universitas Muhammadiyah Surabaya
  • State University of Semarang
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Rekan penulisOrganisasiArtikel bersama
Trias MahmudionoUniversitas Airlangga4
Diah IndrianiAfiliasi tidak diketahui3
Soenarnatalina MelanianiUniversitas Airlangga2
Soenarnatalina MelanianiUniversitas Airlangga2
Rachmah IndawatiUniversitas Airlangga2
Gigih Forda NamaLampung University1
Ayu Dian PamungkasAfiliasi tidak diketahui1
Hery Dian SeptamaLampung University1
Meizano Ardhi MuhammadLampung University1
Wahyu Eko SulistionoLampung University1
Gita Paramita DjausalLampung University1
Muhammad FachrurroziSriwijaya University1
Saparudin SaparudinSriwijaya University1
Erwin ErwinSriwijaya University1
Clara Fin BadillahSriwijaya University1
Junia ErlinaSriwijaya University1
Auzan LazuardiSriwijaya University1
Ninda LutfianiUniversitas Raharja1
Rivialdo Sultan SagaUniversitas Raharja1
Alivia SalmaState University of Semarang1
Emyr Reisha IsauraUniversitas Airlangga1
Sri SumarmiUniversitas Airlangga1
Achmad DzulkifliUniversitas Airlangga1
Achidah Nur SyahdanaAfiliasi tidak diketahui1
Rr. Soenarnatalina MelanianiUniversitas Airlangga1
Yulianto YuliantoPoliteknik Kesehatan Kementerian Kesehatan Palembang1
Nursalam NursalamUniversitas Airlangga1
Erika Untari DewiAfiliasi tidak diketahui1
Ni Putu WidariAfiliasi tidak diketahui1
Esti Yunita SariUniversitas Airlangga1
Yohana Fransiska Ning SusianaAfiliasi tidak diketahui1
Maria MexitaliaDiponegoro University1
Hertanto Wahyu SubagioDiponegoro University1
Ferdy Kurniawan CayamiDiponegoro University1
Magdalena SidhartaniDiponegoro University1
Moh Syarofil AnamDiponegoro University1

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Sumber metadata: OAI-PMH (metadata jurnal) https://e-journal.unair.ac.id/IJPH/oai, pertama di-harvest 10 Nov 2026, terakhir terlihat 10 Nov 2026.
Metadata asli (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">A COMPARISON OF M-ESTIMATION AND S-ESTIMATION ON THE FACTORS AFFECTING IR DHF IN EAST JAVA IN 2017</dc:title>
	<dc:creator>Mardiana, Mardiana</dc:creator>
	<dc:creator>Wibowo, Arief</dc:creator>
	<dc:creator>Mahmudah, Mahmudah</dc:creator>
	<dc:creator>Festi W, Pipit</dc:creator>
	<dc:subject xml:lang="en-US">robust regression</dc:subject>
	<dc:subject xml:lang="en-US">outlier</dc:subject>
	<dc:subject xml:lang="en-US">estimation</dc:subject>
	<dc:subject xml:lang="en-US">DHF</dc:subject>
	<dc:description xml:lang="en-US">ABSTRACTRobust regression on M estimation and S estimation is the Ordinary Least Square (OLS) regression on the data outlier. East Java is one of the provinces in Indonesia with a high case fatalitiy rate (1.34%). The raising of  Dengue Haemoragic Fever (DHF) in East Java has been influenced by climate, population density, human behavior, and environmental sanitation. This study aimed to compare robust regression research by using M estimation and  S estimation on the factors that affect IR DHF. This was done to get the best model regression on the data outlier based on the biggest R2 adjusted and the smallest MSE. This study utitlized observational research with a non-reactive research design using secondary data. The independent variable consisted of population density, healthy behavior, healthy living environment house, and precipitation in East Java in 2017. The dependent variable was incident rate of DHF in 2017. The population included 38 regencies in East Java, while the sample was 35 regencies/cities selected using simple random sampling. The analysis used robust regression on M estimation and S estimation weighting by Tukey's Bisquare. Robust regression on S estimation was found to be the best robust regression on data outlier with R2 adjusted (0.996) and MSE (0.229). Robust regression on S estimation  was = 54.826 + 0.011 (population density) – 0.136 (% healthy behavior) - 0,404 (% healthy house ) - 0,005 (precipitation).Some factors that affect IR DHF can be the main focus for the prevention and control of DHF for the government and society.  Keywords: robust regression, outlier, estimation, estimation, DHF</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Airlangga</dc:publisher>
	<dc:date>2021-11-30</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://e-journal.unair.ac.id/IJPH/article/view/19000</dc:identifier>
	<dc:identifier>10.20473/ijph.v16i3.2021.349-362</dc:identifier>
	<dc:source xml:lang="en-US">The Indonesian Journal of Public Health; Vol. 16 No. 3 (2021): THE INDONESIAN JOURNAL OF PUBLIC HEALTH; 349-362</dc:source>
	<dc:source>2540-8836</dc:source>
	<dc:source>1829-7005</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://e-journal.unair.ac.id/IJPH/article/view/19000/pdf</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2021 The Indonesian Journal of Public Health</dc:rights>
</oai_dc:dc>