Vici Handalusiana Husni
Universitas Mataram

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Determinan Pengangguran Terdidik Tahun 2023 Menggunakan Analisis Regresi Logistik Biner Alifya Salsabilla; Luluk Fadliyanti; Vici Handalusiana Husni
Kaganga:Jurnal Pendidikan Sejarah dan Riset Sosial Humaniora Vol. 8 No. 1 (2025): Kaganga: Jurnal Pendidikan Sejarah dan Riset Sosial Humaniora
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/kaganga.v8i1.13760

Abstract

This study aims to determine the effect of gender, age, marital status, job training, work experience and area of ​​residence on educated unemployment in West Nusa Tenggara Province (NTB) in 2023 using binary logistic regression. The method used is binary logistic regression analysis using the Stata 17 application and using data from the National Labor Force Survey (SAKERNAS) in August 2023 with a sample size of 5,807. The results of this study indicate that factors such as gender, age, marital status, job training, work experience, and area of ​​residence have a significant role in determining a person's chances of becoming educated unemployed. This study concludes that female gender, young individuals, individuals with divorced status, individuals who have not received job training, and area of ​​residence have a higher chance of becoming educated unemployed. Meanwhile, marital status that is married, divorced, and individuals with work experience have a smaller chance of becoming educated unemployed. Keywords: Binary Logistic Regression Analysis, Determinants of Educated Unemployment.
Faktor-Faktor yang Mempengaruhi Wanita Menikah Diusia Produktif untuk Bekerja Tahun 2023 Annisa Rizki Amalia; Luluk Fadliyanti; Vici Handalusiana Husni
Kaganga:Jurnal Pendidikan Sejarah dan Riset Sosial Humaniora Vol. 8 No. 1 (2025): Kaganga: Jurnal Pendidikan Sejarah dan Riset Sosial Humaniora
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/kaganga.v8i1.13776

Abstract

This study aims to determine how the level of education, age, income, number of family members and place of residence of respondents affect the participation of productive-age married women to work in 2023 in NTB Province. The method used is binary logistic regression analysis using the Stata 17 application and using SAKERNAS data from August 2023 with a sample size of 5,984. The results of this study illustrate that factors of education, age, number of family members, and place of residence influence women's decisions to work, with higher education and living in urban areas providing greater opportunities, while older age and larger families tend to reduce women's participation in the workforce. This study concludes that variables such as level of education, age, number of family members, and place of residence affect women's opportunities to work. Women with higher levels of education have greater opportunities for work, while women who are older, have more family members, or live in rural areas tend to have fewer opportunities. These factors illustrate how education, age, family responsibilities, and socio-cultural conditions in the residential environment can affect women's participation in the labor market. Keywords: Be of Productive Age to Work, Married Women.