Analysis of the Determinants of the Gender Empowerment Index in West Sumatra 2024 Using the Group Lasso Method
Main Article Content
Abstract
Gender empowerment remains a multidimensional development challenge in West Sumatra, where regional disparities reflect interconnected educational, economic, political, health, demographic, and infrastructural factors. This study aims to model the Gender Empowerment Index (GEI) across 19 regencies and municipalities in West Sumatra in 2024, identify its relevant determinants, and determine the dominant predictor using Group LASSO. A quantitative research design was employed using secondary data from Statistics Indonesia, comprising 22 predictors classified into six dimensions. All 19 regions were included through census sampling. The data were standardised, assessed for multicollinearity, and analysed using Group LASSO, with K-fold cross-validation applied to determine the optimal penalty parameter. The optimal λ value of 0.2392388 retained 14 predictors and produced a mean squared error of 1.190105 and an R² of 0.985264. The proportion of women serving in Regional People’s Representative Councils emerged as the dominant predictor, with the largest coefficient of 0.892008. These findings demonstrate the utility of Group LASSO for selecting relevant predictors in a multidimensional regional dataset and provide empirical evidence for establishing gender-empowerment policy priorities. The results particularly underscore the importance of women’s political representation in efforts to strengthen gender empowerment across West Sumatra.

Citation Metrics:
Downloads
Citation Metrics & Similar Scopus Articles
-
Arnott L. (2027)Reclaiming the Gaze: Vision, Faith, and Gender in Aemilia Lanyer-s Salve Deus Rex JudaeorumExplorations in Renaissance Culture, 52(1), 79-101
-
Meykadeh S. (2027)The effect of gender on L1-L2 syntactic processing in Turkish-Persian balanced Bilinguals using fMRILanguage Related Research, 17(4), 167-202
-
Arango C.M. (2027)Social inequalities and occupational disease in Colombia: An ecological analysis of the 2021 ENCSST and associated determinantsBiomedica, 47(1)
Article Details

Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
References
Akoglu, H. (2018). User’s guide to correlation coefficients. Turkish Journal of Emergency Medicine, 18(3), 91–93. https://doi.org/10.1016/j.tjem.2018.08.001
Aprilianti, S., & Setiadi, Y. (2022). Faktor-Faktor yang Memengaruhi Indeks Pembangunan Gender di Indonesia Tahun 2020. Seminar Nasional Official Statistics, 2022(1), 245–254. https://doi.org/10.34123/semnasoffstat.v2022i1.1351
Ariansyah, F., & Satria, D. (2024). Faktor-Faktor yang Mempengaruhi Partisipasi Tenaga Kerja Wanita di Indonesia. Media Riset Ekonomi Pembangunan (MedREP), 1(4), 738–747. https://medrep.ppj.unp.ac.id/index.php/MedREP/article/view/123
Belhechmi, S., De Bin, R., Rotolo, F., & Michiels, S. (2020). Accounting for grouped predictor variables or pathways in high-dimensional penalized Cox regression models. BMC Bioinformatics, 21, Article 277. https://doi.org/10.1186/s12859-020-03618-y
Buch, G., Schulz, A., Schmidtmann, I., Strauch, K., & Wild, P. S. (2023). A systematic review and evaluation of statistical methods for group variable selection. Statistics in Medicine, 42(3), 331–352. https://doi.org/10.1002/sim.9620
Cahyati, C., Herrhyanto, N., & Puspita, E. (2019). Pemodelan Indeks Pembangunan Gender (IPG) dengan Menggunakan Regresi Probit Ordinal (Studi Kasus IPG Kabupaten/Kota di Pulau Sumatera Tahun 2015). Jurnal EurekaMatika, 7(2), 83–99. https://doi.org/10.17509/jem.v7i2.22137
Dang, X., Huang, S., & Qian, X. (2021). Penalized Cox’s proportional hazards model for high-dimensional survival data with grouped predictors. Statistics and Computing, 31(6), Article 77. https://doi.org/10.1007/s11222-021-10052-4
Daoud, J. I. (2017). Multicollinearity and regression analysis. Journal of Physics: Conference Series, 949, Article 012009. https://doi.org/10.1088/1742-6596/949/1/012009
Hafifa, R., Nabila, D. R., Hanum, N., Asnidar, A., Andiny, P., & Safuridar, S. (2026). Faktor-Faktor yang Mempengaruhi Indeks Pemberdayaan Gender di Provinsi Aceh. Jurnal Ilmiah Ekonomi dan Manajemen, 4(1), 132–143. https://doi.org/10.61722/jiem.v4i1.7151
Huang, J., Breheny, P., & Ma, S. (2012). A selective review of group selection in high-dimensional models. Statistical Science, 27(4), 481–499. https://doi.org/10.1214/12-STS392
Jain, M. (2023). Women empowerment: A multidimensional approach. Journal of Women Empowerment and Studies, 3(4), 36–42. https://doi.org/10.55529/jwes.34.36.42
Kaseng, E. S. (2023). Keberdayaan Perempuan: Konsep Pemberdayaan dalam Pembangunan Masyarakat Berbasis Gender. Jurnal Kajian Sosial dan Budaya: Tebar Science, 7(3), 117–127. https://doi.org/10.36653/jksb.v7i3.178
Kementerian Pemberdayaan Perempuan dan Perlindungan Anak. (2020). Pembangunan Manusia Berbasis Gender Tahun 2020. https://www.kemenpppa.go.id/lib/uploads/list/50a46-pembangunan-manusia-berbasis-gender-2020.pdf
Kurnianingsih, F., Mahadiansar, Putri, R. A., & Azizi, O. R. (2022). Perspektif Analisis Indeks Pemberdayaan Gender Kota Tanjungpinang dalam Masa Pandemi COVID-19. Jurnal Ilmu Sosial dan Humaniora, 11(1), 45–55. https://doi.org/10.23887/jish.v11i1.37594
Mutmainnah, M., Mawarti, I., & Yusnilawati, Y. (2021). Pemberdayaan Perempuan Akseptor KB dalam Mempertahankan Kesehatan, Kualitas Hidup dan Peran yang Optimal dalam Keluarga. Medical Dedication (Medic): Jurnal Pengabdian kepada Masyarakat FKIK UNJA, 4(1), 241–247. https://doi.org/10.22437/medicaldedication.v4i1.13493
Novianti, E. (2019). Kesenjangan Gender Tingkat Pengangguran Terbuka di Indonesia. Jurnal Pendidikan dan Ekonomi, 8(2), 166–174. https://journal.student.uny.ac.id/ekonomi/article/view/13053
Padhilah, R., Herrhyanto, N., & Lukman. (2024). Analisis Regresi Logistik Biner dengan Metode Group LASSO dalam Data Berdimensi Tinggi (Studi Kasus: Indeks Pembangunan Manusia Kota/Kabupaten di Jawa Barat). BIAStatistics Journal of Statistics Theory and Aplication, 18(1), 1–14. https://biastatistics.statistics.unpad.ac.id/?journal=biastatistics&page=article&op=view&path%5B%5D=266
Putrie, D. A., & Rahman, A. (2021). Analisis dan Pemodelan Pendapatan Pekerja Perempuan di Indonesia Menggunakan Data Panel. Seminar Nasional Official Statistics, 2020(1), 1269–1276. https://doi.org/10.34123/semnasoffstat.v2020i1.688
Riadina, B. P., & Sugianto. (2024). Analisis Pengaruh Indikator Kebijakan Moneter terhadap Tingkat Inflasi di Indonesia. Journal of Development Economics and Digitalization, 3(1), 1–16. https://doi.org/10.59664/jded.v3i1.7666
Rusli, A. S., & Magna, M. S. (2023). Faktor-Faktor yang Mempengaruhi Indeks Pemberdayaan Gender (IDG) Kota Magelang Tahun 2011–2021. EVOKASI: Jurnal Kajian Administrasi dan Sosial Terapan, 2(1), 1–10. https://doi.org/10.20961/evokasi.v2i1.778
Salsabila, D., & Hendrawan, M. Y. (2021). Analisis Kondisi Pemberdayaan Gender di Indonesia Tahun 2020 dengan Agglomerative Hierarchical Clustering dan Biplot. Seminar Nasional Official Statistics, 2021(1), 204–213. https://doi.org/10.34123/semnasoffstat.v2021i1.839
Syukri, M. (2023). Gender policies of the new developmental state: The case of Indonesian new participatory village governance. Journal of Current Southeast Asian Affairs, 42(1), 110–133. https://doi.org/10.1177/18681034221149750
Taqwim, S. F., Vaezghasemi, M., Castel-Feced, S., Dewi, F. S. T., & Schröders, J. (2025). The role of women’s empowerment in fertility preferences and outcomes: Analysis of the 2017 Indonesia Demographic and Health Survey. BMC Women’s Health, 25(1), Article 211. https://doi.org/10.1186/s12905-025-03748-6
Valentina, R. F. (2022). Studi tentang Akses Menempuh Pendidikan Tinggi bagi Perempuan. Jurnal Dialektika Pendidikan IPS, 2(2), 35–47. https://doi.org/10.26740/penips.v2i2.47413
Wulandari, I., Notodiputro, K. A., & Sartono, B. (2020). Variable selection in analyzing life infant birth in Indonesia using group lasso and group SCAD. In Proceedings of the 1st International Conference on Statistics and Analytics (ICSA 2019). EAI. https://doi.org/10.4108/eai.2-8-2019.2290485
Yuan, M., & Lin, Y. (2006). Model selection and estimation in regression with grouped variables. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 68(1), 49–67. https://doi.org/10.1111/j.1467-9868.2005.00532.x
Yustie, R., & Prayitno, B. (2024). Faktor Ekonomi dan Sosial yang Mempengaruhi Pemberdayaan Gender. Equilibrium: Jurnal Ekonomi-Manajemen-Akuntansi, 20(1), 80–87. https://doi.org/10.30742/equilibrium.v20i1.3633


















