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Estimasi Komponen Variansi pada Rancangan Faktorial Acak Lengkap Menggunakan Metode Generalized Least Squares

Jurnal Matematika, Statistika dan Komputasi · Vol. 15 No. 2 (2018) · pp. 54–66

DOI
10.20956/jmsk.v15i2.5714
ISSN
2614-8811, 1858-1382
Published
2018-12-20
Publisher
Department of Mathematics, Hasanuddin University
Language
en

Abstract

AbstractsExperiment design is a test or a row of test by using both statistical description and inference statistical. The aim of this test is to change an input to become an output as a respond of the experiment. In the experiment design, variance of factor A, B, AB error of variance are called as variant component. The aim of this study is to estimate variance component on complete random factorial design for fixed model and mixed model by using Generalized Least Squares (GLS)method, where GLS method as a development of Ordinary Least Square method. It used to be applied on data of complete random factorial design, namely like the influence to density pelleting food which is caused by increasing adhesive material and longtime in storage. The results show that there is no influence of increasing adhesive material to the density of pelleting food. In addition, there exist of diversity of longtime of storage and there exists a diversity interaction between adding adhesive material and long of time of storage to the density of pelleting food Keywords: Generalized Least Squares, variance component, complete random factorial design AbstrakPerancangan percobaan adalah suatu uji atau sederet uji baik itu menggunakan statistika deskripsi maupun statistika inferensi, yang bertujuan untuk mengubah peubah input menjadi suatu output yang merupakan respon dari percobaan tersebut. Dalam perancangan percobaan, variansi dari faktor A, variansi dari faktor B, variansi interaksi faktor AB, dan variansi galat disebut dengan komponen varian. Penelitian ini bertujuan untuk mengestimasi komponen variansi pada rancangan faktorial acak lengkap model tetap dan model campuran menggunakan metode Generalized Least Squares (GLS), dimana metode GLS adalah pengembangan dari metode Ordinary Least Square yang biasa digunakan untuk mengatasi asumsi homogenitas yang biasa dilanggar dalam perancangan percobaan. Metode tersebut diterapkan pada data rancangan faktorial acak lengkap yaitu pengaruh berat jenis pakan pellet dengan kombinasi perlakuan penambahan bahan perekat dan lama penyimpanan. Hasil menunjukkan bahwa tidak terdapat pengaruh penambahan bahan perekat terhadap berat jenis pakan pellet. Selain itu, terdapat keragaman faktor lama penyimpan dan terdapat keragaman interaksi antara faktor penambahan perekat dan lama penyimpanan terhadap berat jenis pakan pellet. Kata kunci: Generalized Least Squares, komponen variansi, rancangan faktorial acak lengkap

Keywords

Collaboration network of the authors

40 authors · 123 co-authorship links · showing the 40 most connected

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

  • Sultan Ageng Tirtayasa University
  • Institut Agama Islam Negeri Kendari
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Anisa AnisaSultan Ageng Tirtayasa University7
Anna IslamiyatiAffiliation unknown5
Erna Tri HerdianiAffiliation unknown5
Siswanto SiswantoAffiliation unknown4
Nirwan IlyasAffiliation unknown3
Nasrah SirajangAffiliation unknown3
Sitti SahrimanAffiliation unknown3
RaupongAffiliation unknown2
Andi Kresna JayaAffiliation unknown2
Andi Isna YunitaAffiliation unknown2
Muhammad FadilAffiliation unknown2
Fauziah NurhidayahAffiliation unknown2
Anni Ivoni ParapaAffiliation unknown2
Zhazha Alifkhamulki RamdhaniAffiliation unknown1
Samsul ArifinAffiliation unknown1
Andi Sitti Fahmi Riyanti HufainiAffiliation unknown1
Dwicahyo Ramadhan PriyatnaAffiliation unknown1
La Podje TalangkoAffiliation unknown1
Vieri KoerniawanAffiliation unknown1
Nurtiti SunusiAffiliation unknown1
Iis Cendrah KasihAffiliation unknown1
Dewi Rahma EnteAffiliation unknown1
Ika FitrianaAffiliation unknown1
Asti Inayati MagfirahAffiliation unknown1
Mega Selvia TjahayaAffiliation unknown1
Andi Tenri Riski AmaliaAffiliation unknown1
Fitri AnnisaAffiliation unknown1
Nur Alfianingsih RajaAffiliation unknown1
Aqilah Salsabila RahmanAffiliation unknown1
Nurhidaya LAffiliation unknown1
Hendriete Tiur Marowi WaibusiAffiliation unknown1
Victor LimanAffiliation unknown1
Sonya SonyaAffiliation unknown1
Asnidar AsnidarAffiliation unknown1
Anisa KalondengAffiliation unknown1
Surya Cahyadi SyamAffiliation unknown1
Nurul HikmahInstitut Agama Islam Negeri Kendari1

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/jmsk/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Estimasi  Komponen Variansi pada Rancangan Faktorial Acak Lengkap Menggunakan Metode Generalized Least Squares</dc:title>
	<dc:creator xml:lang="en">Angriany, A. Muthiah Nur</dc:creator>
	<dc:creator xml:lang="en">Tinungki, Georgina Maria</dc:creator>
	<dc:creator xml:lang="en">Raupong, Raupong</dc:creator>
	<dc:subject xml:lang="en">Generalized Least Squares</dc:subject>
	<dc:subject xml:lang="en">variance component</dc:subject>
	<dc:subject xml:lang="en">complete random factorial design</dc:subject>
	<dc:description xml:lang="en">AbstractsExperiment design is a test or a row of test by using both statistical description and inference statistical. The aim of this test is to change an input to become an output as a respond of the experiment. In the experiment design, variance of factor A, B , AB error of variance are called as variant component. The aim of this study is to estimate variance component on complete random factorial design for fixed model and mixed model by using Generalized Least Squares (GLS)method, where GLS method as a development of Ordinary Least Square method. It used to be applied on data of complete random factorial design, namely like the influence to density pelleting food which is caused by increasing adhesive material and longtime in storage. The results  show that there is no influence of increasing adhesive material to the density of pelleting food. In addition, there exist of diversity of longtime of storage and there exists a diversity  interaction between adding adhesive material and long of time of storage to the density of pelleting food Keywords: Generalized Least Squares, variance component, complete random factorial design AbstrakPerancangan percobaan adalah suatu uji atau sederet uji baik itu menggunakan statistika deskripsi maupun statistika inferensi, yang bertujuan untuk mengubah peubah input menjadi suatu output yang merupakan respon dari percobaan tersebut. Dalam perancangan percobaan,  variansi dari faktor A, variansi dari faktor B, variansi interaksi faktor AB, dan variansi galat disebut dengan komponen varian. Penelitian ini bertujuan untuk mengestimasi komponen variansi pada rancangan faktorial acak lengkap model tetap dan model campuran  menggunakan metode Generalized Least Squares (GLS), dimana metode GLS adalah pengembangan dari metode Ordinary Least Square yang biasa  digunakan untuk mengatasi asumsi homogenitas yang biasa dilanggar dalam perancangan percobaan. Metode tersebut  diterapkan pada data rancangan faktorial acak lengkap yaitu pengaruh berat jenis pakan pellet dengan kombinasi perlakuan penambahan bahan perekat dan lama penyimpanan. Hasil menunjukkan bahwa tidak terdapat pengaruh penambahan bahan perekat terhadap berat jenis pakan pellet. Selain itu, terdapat keragaman faktor lama penyimpan dan terdapat keragaman interaksi  antara faktor penambahan perekat dan lama penyimpanan terhadap berat jenis pakan pellet. Kata kunci: Generalized Least Squares, komponen variansi, rancangan faktorial acak lengkap </dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2018-12-20</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/jmsk/article/view/5714</dc:identifier>
	<dc:identifier>10.20956/jmsk.v15i2.5714</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 15 No. 2 (2019): JMSK Vol. 15, No. 2, January 2019; 54-66</dc:source>
	<dc:source>2614-8811</dc:source>
	<dc:source>1858-1382</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/jmsk/article/view/5714/3160</dc:relation>
	<dc:relation>10.20956/j.v15i2.5714.g3160</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2018 Jurnal Matematika Statistika dan Komputasi</dc:rights>
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