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COMPARISON OF RESAMPLING EFFICIENCY LEVELS OF JACKKNIFE AND DOUBLE JACKKNIFE IN PATH ANALYSIS

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 17 No. 2 (2023) · hlm. 0807–0818

DOI
10.30598/barekengvol17iss2pp0807-0818
ISSN
2615-3017, 1978-7227
Terbit
2023-06-11
Penerbit
PATTIMURA UNIVERSITY
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

The assumption of normality is often not fulfilled, this causes the estimation of the resulting parameters to be less efficient. The problem with assuming that normality is not satisfied can be overcome by resampling. The use of resampling allows data to be applied free of distributional assumptions. In this study, a research simulation was carried out by applying Jackknife resampling and Double Jackknife resampling in path analysis with the assumption that the normality of the residuals was not fulfilled and the number of resampling was set at 100 with the degree of closeness level of relationship between variables consisting of low closeness, medium closeness, and high closeness. Based on the simulation results, resampling with a power of 100 can overcome the problem of unfulfilled normality assumptions. In addition, the comparison of the relative efficiency level of the resampling jackknife and double jackknife in the path analysis obtained by the resampling double jackknife has more efficiency than the resampling jackknife

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  • Universitas Halu Oleo
  • University of Brawijaya
  • Institut Agama Islam Negeri Kendari
  • Universitas Muhammadiyah Parepare
  • Jenderal Soedirman University
  • Universitas Islam Negeri Mahmud Yunus Batusangkar
  • Afiliasi tidak diketahui
  • Organisasi berbeda
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Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Adji Achmad Rinaldo FernandesUniversity of Brawijaya8
Jopang JopangUniversitas Halu Oleo3
Akhyar AbdullahUniversitas Halu Oleo3
Atiek IrianyUniversity of Brawijaya3
Ni Wayan Surya WardhaniUniversity of Brawijaya3
Makmur KambolongUniversitas Halu Oleo2
Mustakim MustakimUniversitas Muhammadiyah Parepare2
Erni QomariyahAfiliasi tidak diketahui2
Achmad EfendiAfiliasi tidak diketahui2
Suci AstutikUniversity of Brawijaya2
Agus Fachrur RozyUniversity of Brawijaya1
Agus SusiloAfiliasi tidak diketahui1
Galuh Wilujeng PuspaAfiliasi tidak diketahui1
Miftakhul CahyatiAfiliasi tidak diketahui1
Dodyk PranowoAfiliasi tidak diketahui1
Sumardona SumardonaInstitut Agama Islam Negeri Kendari1
Sarlinda SarlindaInstitut Agama Islam Negeri Kendari1
Epiyana EpiyanaInstitut Agama Islam Negeri Kendari1
Sarnianti SarniantiInstitut Agama Islam Negeri Kendari1
Kamrin KamrinUniversitas Halu Oleo1
Ruslan MajidUniversitas Halu Oleo1
Megasari SidulaAfiliasi tidak diketahui1
Nooraini AsrudinAfiliasi tidak diketahui1
Suriyani Bunga BataraAfiliasi tidak diketahui1
Siti NurhayatiJenderal Soedirman University1
Nyoman Ningsih UtamiAfiliasi tidak diketahui1
Candra Puspita NingtyasAfiliasi tidak diketahui1
Aprilia WulandariAfiliasi tidak diketahui1
Santi M Santi MAfiliasi tidak diketahui1
isran museAfiliasi tidak diketahui1
Aminuddin AminuddinInstitut Agama Islam Negeri Kendari1
Dewi DewiAfiliasi tidak diketahui1
Muh AmirUniversitas Halu Oleo1
muslima kurniatiAfiliasi tidak diketahui1
Abdul KadirUniversitas Halu Oleo1
Mirab MirabAfiliasi tidak diketahui1
Irwan IrwanUniversitas Islam Negeri Mahmud Yunus Batusangkar1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 5 Nov 2026.
Metadata asli (oai_dc)
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	<dc:title xml:lang="en-US">COMPARISON OF RESAMPLING EFFICIENCY LEVELS OF JACKKNIFE AND DOUBLE JACKKNIFE IN PATH ANALYSIS</dc:title>
	<dc:creator>Papalia, M. Fikar</dc:creator>
	<dc:creator>Solimun, Solimun</dc:creator>
	<dc:creator>Nurjannah, Nurjannah</dc:creator>
	<dc:description xml:lang="en-US">The assumption of normality is often not fulfilled, this causes the estimation of the resulting parameters to be less efficient. The problem with assuming that normality is not satisfied can be overcome by resampling. The use of resampling allows data to be applied free of distributional assumptions. In this study, a research simulation was carried out by applying Jackknife resampling and Double Jackknife resampling in path analysis with the assumption that the normality of the residuals was not fulfilled and the number of resampling was set at 100 with the degree of closeness level of relationship between variables consisting of low closeness, medium closeness, and high closeness. Based on the simulation results, resampling with a power of 100 can overcome the problem of unfulfilled normality assumptions. In addition, the comparison of the relative efficiency level of the resampling jackknife and double jackknife in the path analysis obtained by the resampling double jackknife has more efficiency than the resampling jackknife</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2023-06-11</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://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7805</dc:identifier>
	<dc:identifier>10.30598/barekengvol17iss2pp0807-0818</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications; 0807-0818</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol17iss2year2023</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>info:eu-repo/grantAgreement/EC/FP7/123456</dc:relation>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7805/5942</dc:relation>
	<dc:rights xml:lang="en-US">info:eu-repo/semantics/openAccess</dc:rights>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 M. Fikar Papalia, Solimun Solimun, Nurjannah Nurjannah</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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