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Management Multivariate Analysis Methods for Variables Measurement in Scientific Papers

APTISI Transactions on Management (ATM) · Vol. 3 No. 1 (2019) · hlm. 65–72

DOI
10.33050/atm.v3i1.826
ISSN
2622-6804, 2622-6812
Terbit
2019-01-03
Penerbit
Pandawan
Bahasa
en
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Inggris

The management of writing a scientific papers we already know has important chapters in the writing. And have a way of choosing in a variety of methods. There are problems in this study, namely the absence of the use of research methods in scientific-rich management. Then one of them is needed by multivariate data analysis management to become one of the methods in writing scientific papers. Multivariate data is data collected from two or more observations by measuring these observations with several characteristics. There are 2 (two) methods in multivariate data, namely dependency and interdependence methods. Dependency analysis functions to explain or predict dependent variables by using two or more independent variables. Focused on the dependency method there are 9 (nine) classifications. It is expected that the multivariate data analysis management can help writers to use scientific research methods well and be able to analyze the influence of several variables on other variables at the same time

Bahasa Indonesia

The management of writing a scientific papers we already know has important chapters in the writing. And have a way of choosing in a variety of methods. There are problems in this study, namely the absence of the use of research methods in scientific-rich management. Then one of them is needed by multivariate data analysis management to become one of the methods in writing scientific papers. Multivariate data is data collected from two or more observations by measuring these observations with several characteristics. There are 2 (two) methods in multivariate data, namely dependency and interdependence methods. Dependency analysis functions to explain or predict dependent variables by using two or more independent variables. Focused on the dependency method there are 9 (nine) classifications. It is expected that the multivariate data analysis management can help writers to use scientific research methods well and be able to analyze the influence of several variables on other variables at the same time

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6 penulis · 9 tautan kepenulisan bersama · 6 lintas organisasi

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  • Universitas Hang Tuah
  • Universiti Utara Malaysia
  • Universitas Raharja
  • Universitas Airlangga
  • Organisasi berbeda
  • Organisasi sama
  • Afiliasi tidak diketahui
  • Garis lebih tebal = lebih banyak artikel bersama · lingkaran lebih besar = lebih banyak artikel
Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Meity ArdianaUniversitas Hang Tuah1
Adriano AdrianoUniversitas Hang Tuah1
Kurniadi DoniUniversitas Airlangga1

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://ijc.ilearning.co/ATM/oai, pertama di-harvest 6 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en">Management Multivariate Analysis Methods for Variables Measurement in Scientific Papers</dc:title>
	<dc:title xml:lang="id">Management Multivariate Analysis Methods for Variables Measurement in Scientific Papers</dc:title>
	<dc:creator xml:lang="en">Yulianto, Yulianto</dc:creator>
	<dc:creator xml:lang="en">Robihaningrum, Namira</dc:creator>
	<dc:creator xml:lang="en">Elinda, Bella Dhea</dc:creator>
	<dc:subject xml:lang="en">Management</dc:subject>
	<dc:subject xml:lang="en">Multivariate Data</dc:subject>
	<dc:subject xml:lang="en">Scientific Paper</dc:subject>
	<dc:subject xml:lang="id">Management</dc:subject>
	<dc:subject xml:lang="id">Multivariate Data</dc:subject>
	<dc:subject xml:lang="id">Scientific Paper</dc:subject>
	<dc:description xml:lang="en">The management of writing a scientific papers we already know has important chapters in the writing. And have a way of choosing in a variety of methods. There are problems in this study, namely the absence of the use of research methods in scientific-rich management. Then one of them is needed by multivariate data analysis management to become one of the methods in writing scientific papers. Multivariate data is data collected from two or more observations by measuring these observations with several characteristics. There are 2 (two) methods in multivariate data, namely dependency and interdependence methods. Dependency analysis functions to explain or predict dependent variables by using two or more independent variables. Focused on the dependency method there are 9 (nine) classifications. It is expected that the multivariate data analysis management can help writers to use scientific research methods well and be able to analyze the influence of several variables on other variables at the same time</dc:description>
	<dc:description xml:lang="id">The management of writing a scientific papers we already know has important chapters in the writing. And have a way of choosing in a variety of methods. There are problems in this study, namely the absence of the use of research methods in scientific-rich management. Then one of them is needed by multivariate data analysis management to become one of the methods in writing scientific papers. Multivariate data is data collected from two or more observations by measuring these observations with several characteristics. There are 2 (two) methods in multivariate data, namely dependency and interdependence methods. Dependency analysis functions to explain or predict dependent variables by using two or more independent variables. Focused on the dependency method there are 9 (nine) classifications. It is expected that the multivariate data analysis management can help writers to use scientific research methods well and be able to analyze the influence of several variables on other variables at the same time</dc:description>
	<dc:publisher xml:lang="en">Pandawan</dc:publisher>
	<dc:date>2019-01-03</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://ijc.ilearning.co/ATM/article/view/826</dc:identifier>
	<dc:identifier>10.33050/atm.v3i1.826</dc:identifier>
	<dc:source xml:lang="en">APTISI Transactions on Management (ATM); Vol. 3 No. 1 (2019): January; 65-72</dc:source>
	<dc:source xml:lang="id">APTISI Transactions on Management (ATM); Vol 3 No 1 (2019): ATM (APTISI Transactions on Management); 65-72</dc:source>
	<dc:source>2622-6804</dc:source>
	<dc:source>2622-6812</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://ijc.ilearning.co/ATM/article/view/826/195</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2019 Yulianto Yulianto, Namira Robihaningrum, Bella Dhea Elinda (Author)</dc:rights>
	<dc:rights xml:lang="en">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>