Application of Firth’s Logistic Regression in Analyzing Employment Status of Educated Women in Riau
Keywords: educated women, employment status, Firth's logistic regression
Abstract
The ongoing demographic bonus in Indonesia provides a strategic opportunity to promote inclusive development. To optimize this potential, the involvement of educated women is crucial and not just rely on the contribution of men. However, the women’s Labor Force Participation Rate (LFPR) has remained stagnant over the past two decades and gender inequality in employment persists to this day. Riau Province requires the most attention, as in the last three years it has recorded the lowest women’s LFPR nationally. Interestingly, data show that the proportion of educated women who are employed is actually lower than that of less educated women. This study applies Firth’s logistic regression to analyse the employment status of educated women in Riau Province in 2024. The method is employed to reduce estimation bias that may arise from data imbalance. The results indicate that ICT use, age, marital status, and place of residence have significant effects. These findings can support the development of more effective strategies to increase the employment status of educated women, particularly by strengthening ICT access and considering sociodemographic characteristics.
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References
Adriani, D., & Yustini, T. (2021). Anticipating the demographic bonus from the perspective of human capital in Indonesia. International Journal of Research in Business and Social Science (2147- 4478), 10(6), 141–152. https://doi.org/10.20525/ijrbs.v10i6.1377
Amini, F., & Oktora, S. I. (2021). Comorbid of chronic kidney disease (CKD) patients who undergoing dialysis in Indonesia using firth logistic regression. THE 2ND SCIENCE AND MATHEMATICS INTERNATIONAL CONFERENCE (SMIC 2020): Transforming Research and Education of Science and Mathematics in the Digital Age, 020009. https://doi.org/10.1063/5.0041667
BPS. (2022). Keadaan angkatan kerja Indonesia Agustus 2022.
BPS. (2023). Keadaan angkatan kerja Indonesia Agustus 2023.
BPS. (2024a). Indeks Pembangunan Teknologi Informasi dan Komunikasi 2024.
BPS. (2024b). Keadaan angkatan kerja Indonesia Agustus 2024.
BPS. (2024c). Keadaan angkatan kerja Riau Agustus 2024.
BPS. (2024d). Persentase penduduk usia 25 Tahun keatas dengan pendidikan SMA ke atas menurut jenis kelamin (Persen), 2024. BPS. https://www.bps.go.id/id/statistics-table/2/MjE5OSMy/persentasependuduk-usia-25-tahun-keatas-dengan-pendidikan-sma-ke-atas-menurut-jeniskelamin--persen-
Damayanti, K. (2021). Determinan perempuan bekerja di Jawa Barat. Jurnal Kependudukan Indonesia, 16(1), 55–66. https://doi.org/10.14203/jki.v16i1.428
Firth, D. (1993). Bias Reduction of Maximum Likelihood Estimates. Biometrika, 80(1), 27–38. https://doi.org/10.2307/2336755
Gaffari, A., & Handayani, D. (2019). Keputusan usia muda yang tidak bekerja dan tidak terikat pendidikan (nee) dan karakteristiknya di Indonesia. Jurnal Ekonomi, 22(2), 76–91.
Hosmer, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied Logistic Regression. Wiley. https://doi.org/10.1002/9781118548387
Koto, R., Ridwan, E., & Muharja, F. (2025). Analisis Partisipasi Angkatan Kerja Perempuan di Indonesia. Jurnal Informatika Ekonomi Bisnis, 7(3), 607–612. https://doi.org/10.37034/infeb.v7i3.1221
Kurniasih, C. E., Tampubolon, D., & Ula, T. (2022). Analisis Pengaruh Indikator Pasar Tenaga Kerja Perempuan Terhadap Kemiskinan Antar Kabupaten/Kota di Provinsi Riau. National Multidisciplinary Sciences, 1(4), 572–584. https://doi.org/10.32528/nms.v1i4.109
Kusumawardhani, N., Pramana, R., Saputri, N. S., & Suryadarma, D. (2023). Heterogeneous impact of internet availability on female labor market outcomes in an emerging economy: Evidence from Indonesia. World Development, 164, 106182. https://doi.org/10.1016/j.worlddev.2022.106182
La Ode, M. H. (2023). Durasi Mencari Kerja Bagi Pekerja Usia Muda di Indonesia. Jurnal Forum Analisis Statistik (FORMASI), 2(2), 118–128. https://doi.org/10.57059/formasi.v2i2.38
Lusiyanti, L., & Wicaksono, P. (2020). The Impact of Education and Social Demographic Factors on Female Labor Force Participation in Indonesia. Muwazah, 12(2), 219–236.
Mankiw, N. Gregory., & Harris, R. B. (1998). Principles of microeconomics. Dryden Press.
McQuaid, R. W., & Lindsay, C. (2005). The Concept of Employability. Urban Studies, 42(2), 197–219. https://doi.org/10.1080/0042098042000316100
Mulugeta, G. (2021). The role and determinants of women labor force participation for household poverty reduction in Debre Birhan town, North Shewa zone, Ethiopia. Cogent Economics & Finance, 9(1). https://doi.org/10.1080/23322039.2021.1892927
Ngoa, G. B. N., & Song, J. S. (2021). Female participation in African labor markets: The role of information and communication technologies. Telecommunications Policy, 45(9), 102174. https://doi.org/10.1016/j.telpol.2021.102174
Nikulin, D. (2017). The Impact of ICTs on Women’s Economic Empowerment. In Catalyzing Development through ICT Adoption (pp. 15–24). Springer International Publishing. https://doi.org/10.1007/978-3-319-56523-1_2
Niu, L. (2020). A review of the application of logistic regression in educational research: common issues, implications, and suggestions. Educational Review, 72(1), 41–67. https://doi.org/10.1080/00131911.2018.1483892
Potgieter, I. L. (2021). Surviving the Digital Era: The Link Between Positive Coping, Workplace Friendships and Career Adaptability. In Agile Coping in the Digital Workplace (pp. 57–78). Springer International Publishing. https://doi.org/10.1007/978-3-030-70228-1_4
Shah, G. H., Etheredge, G. D., Schwind, J. S., Maluantesa, L., Waterfield, K. C., Mulenga, A., Ikhile, O., Engetele, E., & Ayangunna, E. (2022). Firth’s Logistic Regression of Interruption in Treatment before and after the Onset of COVID-19 among People Living with HIV on ART in Two Provinces of DRC. Healthcare, 10(8), 1516. https://doi.org/10.3390/healthcare10081516
Shantika, F. (2019). Analisis peran ganda pada perempuan terdidik dalam perspektif sosial - ekonomi dan etnis di Indonesia [Thesis]. Universitas Brawijaya.
Suhaib, A. M., & Kartiasih, F. (2024). Pengaruh Teknologi Digital terhadap Partisipasi Perempuan dalam Angkatan Kerja di Provinsi Papua. Jurnal Ketenagakerjaan, 19(2), 218–232. https://doi.org/10.47198/jnaker.v19i2.342
Tsaniyah, A. H., & Sugiharti, L. (2021). The determinants of women’s work: a case study in East Java. Jurnal Ilmu Ekonomi Terapan, 6(1), 66–81.
World Bank. (2011). World Development Report: Gender Equality in Indonesia Improving. World Bank. https://www.worldbank.org/en/news/press-release/2011/09/20/world-development-report-gender-equality-indonesia-improving
Yin, J., & Tian, L. (2014). Joint inference about sensitivity and specificity at the optimal cut-off point associated with Youden index. Computational Statistics & Data Analysis, 77, 1–13. https://doi.org/10.1016/j.csda.2014.01.021
Youden, W. J. (1950). Index for rating diagnostic tests. Cancer, 3(1), 32–35.
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