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Estimasi Parameter Model Three-Factor Completely Randomized Design dengan Metode Robust MM

ESTIMASI: Journal of Statistics and Its Application · Vol. 6 No. 1 (2025) · pp. 1–9

DOI
10.20956/ejsa.v6i1.18323
ISSN
2721-379X, 2721-3803
Published
2025-02-17
Publisher
Hasanuddin University
Language
en

Abstract

When conducting experiments, it is often found that there are errors in the observed responses. It can cause data outliers to appear whose existence results in making conclusions inaccurate. Therefore, outliers need to be overcome by applying the robust regression method. The robust method used is the robust MM because it has a high level of efficiency and breakdown point. The Robust MM method is useful for obtaining parameter estimates in a three-factor Completely Randomized Design (CRD) which is applied to the data on average abdominal fat of broiler chickens experiencing outliers in four observations. The results showed that the presence of outliers caused no effect of differences in age of chicken and the interaction between age of chicken and feeding fermented kiambang on the average abdominal fat of broiler chickens. However, after the data was replaced with estimated data obtained from the Robust MM method to overcome outliers, it showed that there was an effect of age of chicken and the interaction between age of chicken and feeding of fermented kiambang on the average abdominal fat of broiler chickens.

Keywords

Collaboration network of the authors

34 authors · 100 co-authorship links

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  • Institut Agama Islam Negeri Kendari
  • Affiliation unknown
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Co-authorOrganisationJoint articles
Georgina Maria TinungkiAffiliation unknown3
Erna Tri HerdianiAffiliation unknown2
Anna IslamiyatiAffiliation unknown2
Nirwan IlyasAffiliation unknown2
Iis Cendrah KasihAffiliation unknown1
Andi Kresna JayaAffiliation unknown1
Reski AmalahAffiliation unknown1
Ratmila MammiAffiliation unknown1
Nur Alfianingsih RajaAffiliation unknown1
Fitri FitriAffiliation unknown1
Sitti SahrimanAffiliation unknown1
Mukrimin AdamAffiliation unknown1
Nurul IkhsaniAffiliation unknown1
RaupongAffiliation unknown1
SuritmanAffiliation unknown1
Surya Cahyadi SyamAffiliation unknown1
Siswanto SiswantoAffiliation unknown1
Afifah Mutiah NurdinAffiliation unknown1
Muh. Indirwan ArfanAffiliation unknown1
Nuralyatussa’ adaAffiliation unknown1
Nurul HikmahInstitut Agama Islam Negeri Kendari1
Raupong RaupongAffiliation unknown1
Parida Ayu NingsiAffiliation unknown1
Kevin Ekarinaldo PalunganAffiliation unknown1
Muhammad FadilAffiliation unknown1
Andi M Alfin BasoAffiliation unknown1
A. Elisha WulandariAffiliation unknown1
Belia Nurul FajriAffiliation unknown1
Abdullah PannuAffiliation unknown1
Alfian Akbar VallarinoAffiliation unknown1
Anugrah Nur Isnaeni RahmanAffiliation 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://journal.unhas.ac.id/index.php/ESTIMASI/oai, first harvested 2 Nov 2026, last seen 2 Nov 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en">Estimasi Parameter Model Three-Factor Completely Randomized Design dengan Metode Robust MM</dc:title>
	<dc:creator xml:lang="en">Nurkamalia, Nurkamalia</dc:creator>
	<dc:creator xml:lang="en">Kalondeng, Anisa</dc:creator>
	<dc:creator xml:lang="en">Sirajang, Nasrah</dc:creator>
	<dc:subject xml:lang="en">Three-Factor Completely Randomized Design</dc:subject>
	<dc:subject xml:lang="en">Outliers</dc:subject>
	<dc:subject xml:lang="en">Robust  Regression</dc:subject>
	<dc:subject xml:lang="en">MM Robust Method</dc:subject>
	<dc:description xml:lang="en">When conducting experiments, it is often found that there are errors in the observed responses. It can cause data outliers to appear whose existence results in making conclusions inaccurate. Therefore, outliers need to be overcome by applying the robust regression method. The robust method used is the robust MM because it has a high level of efficiency and breakdown point. The Robust MM method is useful for obtaining parameter estimates in a three-factor Completely Randomized Design (CRD) which is applied to the data on average abdominal fat of broiler chickens experiencing outliers in four observations. The results showed that the presence of outliers caused no effect of differences in age of chicken and the interaction between age of chicken and feeding fermented kiambang on the average abdominal fat of broiler chickens. However, after the data was replaced with estimated data obtained from the Robust MM method to overcome outliers, it showed that there was an effect of age of chicken and the interaction between age of chicken and feeding of fermented kiambang on the average abdominal fat of broiler chickens. </dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2025-02-17</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://journal.unhas.ac.id/index.php/ESTIMASI/article/view/18323</dc:identifier>
	<dc:identifier>10.20956/ejsa.v6i1.18323</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 6, No. 1, Januari, 2025 : Estimasi; 1-9</dc:source>
	<dc:source>2721-379X</dc:source>
	<dc:source>2721-3803</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/18323/12545</dc:relation>
</oai_dc:dc>