Pemodelan Status Usaha (Pengusaha dan Pekerja/Karyawan) Menggunakan Regresi Logistik Multilevel

The level of a country's economy is directly proportional to the number of entrepreneurs in the country. According to the World Bank standard number of entrepreneurs, the ideal of a country is at least 4% of the total population. Based on data from the Indonesian Young Entrepreneurs Association...

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Autor principal:	eko yulian
Formato:	article
Lenguaje:	EN
Publicado:	Department of Mathematics, UIN Sunan Ampel Surabaya 2017
Materias:	Enterpreneur, Logistic regression; Multilevel model Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/1afa6f823e02423b83cc3cc42cbe7ea4
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spelling	oai:doaj.org-article:1afa6f823e02423b83cc3cc42cbe7ea42021-12-02T17:16:57ZPemodelan Status Usaha (Pengusaha dan Pekerja/Karyawan) Menggunakan Regresi Logistik Multilevel2527-31592527-316710.15642/mantik.2017.3.1.30-38https://doaj.org/article/1afa6f823e02423b83cc3cc42cbe7ea42017-10-01T00:00:00Zhttp://jurnalsaintek.uinsby.ac.id/index.php/mantik/article/view/160https://doaj.org/toc/2527-3159https://doaj.org/toc/2527-3167The level of a country's economy is directly proportional to the number of entrepreneurs in the country. According to the World Bank standard number of entrepreneurs, the ideal of a country is at least 4% of the total population. Based on data from the Indonesian Young Entrepreneurs Association (HIPMI), the number of entrepreneurs in Indonesia is only about 1.5%. Of course not easy to achieve the ideal number of bank standards-based world that is 4%. This study aims to determine what factors are driving someone in determining a career as an entrepreneur or not (worker/employee). The data used is the Adult Population Survey (APS) in 2013 conducted by the Global Entrepreneurship Monitor (GEM). the survey conducted in 16 provinces, 51 districts/cities, and 176 subdistricts. Data generated hierarchical modeling that will be performed using multilevel logistic regression. The variables studied were the state variable effort (Y), variable knowent (X1), variable opport (X2), variable suskill (X3), variable fearfail (X4), the variable gender (X5) at level 1 and the variable sub-district at level 2. the analysis showed that the logistic regression model 2-level produce a better model than the ordinary logistic regression model. Based on modeling results we concluded that all predictor variables (knowent, opport, suskill, fearfail, gender, etc.) affect the status of one's business.eko yulianDepartment of Mathematics, UIN Sunan Ampel SurabayaarticleEnterpreneur, Logistic regression; Multilevel modelMathematicsQA1-939ENMantik: Jurnal Matematika, Vol 3, Iss 1, Pp 30-38 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Enterpreneur, Logistic regression; Multilevel model Mathematics QA1-939
spellingShingle	Enterpreneur, Logistic regression; Multilevel model Mathematics QA1-939 eko yulian Pemodelan Status Usaha (Pengusaha dan Pekerja/Karyawan) Menggunakan Regresi Logistik Multilevel
description	The level of a country's economy is directly proportional to the number of entrepreneurs in the country. According to the World Bank standard number of entrepreneurs, the ideal of a country is at least 4% of the total population. Based on data from the Indonesian Young Entrepreneurs Association (HIPMI), the number of entrepreneurs in Indonesia is only about 1.5%. Of course not easy to achieve the ideal number of bank standards-based world that is 4%. This study aims to determine what factors are driving someone in determining a career as an entrepreneur or not (worker/employee). The data used is the Adult Population Survey (APS) in 2013 conducted by the Global Entrepreneurship Monitor (GEM). the survey conducted in 16 provinces, 51 districts/cities, and 176 subdistricts. Data generated hierarchical modeling that will be performed using multilevel logistic regression. The variables studied were the state variable effort (Y), variable knowent (X1), variable opport (X2), variable suskill (X3), variable fearfail (X4), the variable gender (X5) at level 1 and the variable sub-district at level 2. the analysis showed that the logistic regression model 2-level produce a better model than the ordinary logistic regression model. Based on modeling results we concluded that all predictor variables (knowent, opport, suskill, fearfail, gender, etc.) affect the status of one's business.
format	article
author	eko yulian
author_facet	eko yulian
author_sort	eko yulian
title	Pemodelan Status Usaha (Pengusaha dan Pekerja/Karyawan) Menggunakan Regresi Logistik Multilevel
title_short	Pemodelan Status Usaha (Pengusaha dan Pekerja/Karyawan) Menggunakan Regresi Logistik Multilevel
title_full	Pemodelan Status Usaha (Pengusaha dan Pekerja/Karyawan) Menggunakan Regresi Logistik Multilevel
title_fullStr	Pemodelan Status Usaha (Pengusaha dan Pekerja/Karyawan) Menggunakan Regresi Logistik Multilevel
title_full_unstemmed	Pemodelan Status Usaha (Pengusaha dan Pekerja/Karyawan) Menggunakan Regresi Logistik Multilevel
title_sort	pemodelan status usaha (pengusaha dan pekerja/karyawan) menggunakan regresi logistik multilevel
publisher	Department of Mathematics, UIN Sunan Ampel Surabaya
publishDate	2017
url	https://doaj.org/article/1afa6f823e02423b83cc3cc42cbe7ea4
work_keys_str_mv	AT ekoyulian pemodelanstatususahapengusahadanpekerjakaryawanmenggunakanregresilogistikmultilevel
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Pemodelan Status Usaha (Pengusaha dan Pekerja/Karyawan) Menggunakan Regresi Logistik Multilevel

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