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Perbandingan Uji Likelihood Ratio Dan Uji F Asymtotik Pada Regresi Linier

Jurnal Pembelajaran Berpikir Matematika (Journal of Mathematics Thinking Learning) · Vol. 5 No. 2 (2020)

DOI
10.33772/jpbm.v5i2.15032
ISSN
2502-3284
Published
2020-09-11
Publisher
Universitas Halu Oleo
Language
eng
License
creativecommons.org/licenses/by/4.0

Abstract

Abstrak: Analisis regresi adalah studi mengenai ketergantungan satu variabel terikat dengan satu atau lebih variabel bebas, dengan tujuan mengestimasi dan memprediksi rata-rata populasi atau nilai rata-rata variabel terikat berdasarkan nilai variabel bebas yang diketahui. Terdapat berbagai uji hipotesis yang dapat digunakan untuk menentukan model yang cocok untuk untuk mengetahui hubungan antar variabel tidak bebas dengan satu atau lebih variabel bebas, di antarannya adalah uji likelihood ratio dan uji F asimtotik. Uji hipotesis menggunakan uji likelihood ratio, dimana merupakan salah satu uji yang berhubungan langsung dengan penduga maksimum likelihood, yang model distribusi dari populasinya mengikuti model distribusi dengan pdf tertentu dimana diasumsikan normal dibandingkan dengan uji hipotesis menggunakan uji F asymtotik, yang merupakan uji di mana perosedur inferensi secara asimtotik tidak membutuhkan asumsi distribusi dari observasinya. uji hipotesis baik uji likelihood ratio dan uji F asymtotik pada analisis regresi menghasilkan bentuk model yang sama.Kata Kunci: Analisis Regresi, Uji Likelihood ratio, Uji F AsymtotikAbstract: Regression analysis is a study of the dependence of one dependent variable with one or more independent variables, with the aim of estimating and predicting the population mean or average value of the dependent variable based on the known value of the independent variable. There are various hypothesis tests that can be used to determine a suitable model to determine the relationship between dependent variables and one or more independent variables, including the likelihood ratio test and the asymptotic F test. Hypothesis testing uses the likelihood ratio test, which is one of the tests that is directly related to the maximum likelihood estimator, where the distribution model of the population follows a distribution model with a particular pdf which is assumed to be normal compared to the hypothesis test using the asymptotic F test, which is a test in which the inference procedure asymptotically it does not require assuming the distribution of the observations. Hypothesis test both likelihood ratio test and asymptotic F test in regression analysis produces the same model.Key words: Regression Analysis, likelihood ratio test, asymptotic F test.

Collaboration network of the authors

40 authors · 126 co-authorship links · 1 across different organisations · showing the 40 most connected

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

  • Universitas Halu Oleo
  • Universitas Muhammadiyah Buton
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Tamrin TamrinUniversitas Halu Oleo15
Ansharullah AnsharullahUniversitas Halu Oleo9
SRI WAHYUNIAffiliation unknown6
LA KARIMUNAUniversitas Halu Oleo5
SRI REJEKIUniversitas Halu Oleo4
Muhammad Zakir MuzakkarAffiliation unknown4
Muhammad Syukri SadimantaraUniversitas Halu Oleo3
Abdu Rahman BacoAffiliation unknown3
Suwarjoyowirayatno SuwarjoyowirayatnoAffiliation unknown3
Kobajashi Togo IsamuAffiliation unknown3
RH Fitri FaradillaAffiliation unknown3
La RiandaAffiliation unknown2
Djukrana WahabAffiliation unknown2
Sakir SakirAffiliation unknown2
Nur AsyikUniversitas Halu Oleo2
Wa Ode RatnaUniversitas Halu Oleo1
GEDE AGUS SANJAYAUniversitas Halu Oleo1
Nurhaliza NurhalizaUniversitas Halu Oleo1
MARIANI MARIANIUniversitas Halu Oleo1
ADAM MALIKUniversitas Halu Oleo1
H. Abdu Rahman BacoAffiliation unknown1
Hamrin HamrinAffiliation unknown1
Bayu HarisaktiAffiliation unknown1
Mizan Reski ArsandiAffiliation unknown1
Mustamin AnggoUniversitas Halu Oleo1
Kodirun KodirunUniversitas Halu Oleo1
Irma YahyaUniversitas Halu Oleo1
Ahid HidayatUniversitas Halu Oleo1
Gusti N.A. WibawaAffiliation unknown1
Karmila DawistaAffiliation unknown1
Tresia NataliaAffiliation unknown1
Sukma SukmaUniversitas Muhammadiyah Buton1
Wulandari WulandariAffiliation unknown1
Asrul SaniAffiliation unknown1
Jufra JufraAffiliation unknown1
Muh. Kabil DjafarAffiliation unknown1
Norma MukhtarAffiliation 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://ojs.uho.ac.id/index.php/JPBM/oai, first harvested 30 Okt 2026, last seen 1 Nov 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en-US">Perbandingan Uji Likelihood Ratio Dan Uji F Asymtotik Pada Regresi Linier</dc:title>
	<dc:creator>Hermanto, Hermanto</dc:creator>
	<dc:creator>Somayasa, Wayan</dc:creator>
	<dc:creator>Pimpi, La</dc:creator>
	<dc:subject xml:lang="en-US"></dc:subject>
	<dc:description xml:lang="en-US">Abstrak: Analisis regresi adalah studi mengenai ketergantungan satu variabel terikat dengan satu atau lebih variabel bebas, dengan tujuan mengestimasi dan memprediksi rata-rata populasi atau nilai rata-rata variabel terikat berdasarkan nilai variabel bebas yang diketahui. Terdapat berbagai uji hipotesis yang dapat digunakan untuk menentukan model yang cocok untuk untuk mengetahui hubungan antar variabel tidak bebas dengan satu atau lebih variabel bebas, di antarannya adalah uji likelihood ratio dan uji F asimtotik. Uji hipotesis menggunakan uji likelihood ratio, dimana merupakan salah satu uji yang berhubungan langsung dengan penduga maksimum likelihood, yang model distribusi dari populasinya mengikuti model distribusi dengan pdf tertentu dimana diasumsikan normal dibandingkan dengan uji hipotesis menggunakan uji F asymtotik, yang merupakan uji di mana perosedur inferensi secara asimtotik tidak membutuhkan asumsi distribusi dari observasinya. uji hipotesis baik uji likelihood ratio dan uji F asymtotik pada analisis regresi menghasilkan bentuk model yang sama.Kata Kunci: Analisis Regresi, Uji Likelihood ratio, Uji F AsymtotikAbstract: Regression analysis is a study of the dependence of one dependent variable with one or more independent variables, with the aim of estimating and predicting the population mean or average value of the dependent variable based on the known value of the independent variable. There are various hypothesis tests that can be used to determine a suitable model to determine the relationship between dependent variables and one or more independent variables, including the likelihood ratio test and the asymptotic F test. Hypothesis testing uses the likelihood ratio test, which is one of the tests that is directly related to the maximum likelihood estimator, where the distribution model of the population follows a distribution model with a particular pdf which is assumed to be normal compared to the hypothesis test using the asymptotic F test, which is a test in which the inference procedure asymptotically it does not require assuming the distribution of the observations. Hypothesis test both likelihood ratio test and asymptotic F test in regression analysis produces the same model.Key words: Regression Analysis, likelihood ratio test, asymptotic F test.</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Halu Oleo</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2020-09-11</dc:date>
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	<dc:identifier>https://ojs.uho.ac.id/index.php/JPBM/article/view/15032</dc:identifier>
	<dc:identifier>10.33772/jpbm.v5i2.15032</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Pembelajaran Berpikir Matematika (Journal of Mathematics Thinking Learning); Vol 5, No 2 (2020)</dc:source>
	<dc:source>2502-3284</dc:source>
	<dc:source>10.33772/jpbm.v5i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs.uho.ac.id/index.php/JPBM/article/view/15032/pdf</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2020 Jurnal Pembelajaran Berpikir Matematika (Journal of Mathematics Thinking Learning)</dc:rights>
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