Modeling of Regency/City Unemployment Rates in Java Island Using Multilevel Binary Logistic Regression
DOI:
https://doi.org/10.20956/j.v21i1.35584Keywords:
Unemployment Rate, Binary Logistic Regression, Multilevel, Hierarchical DataAbstract
Multilevel binary logistic regression analysis is a development of logistic regression for hierarchical data structures. Hierarchical data is data from a population that has levels. This research examines the relationship model of Life Expectancy, Mean Years of Schooling, Expected Years of Schooling, Regency/City Minimum Wage as explanatory variables at level 1 (Regency) and Gross Regional Domestic Income (GRDP) as an explanatory variable at level 2 (Provincial) against Unemployment Rate (UR) as a response variable. The research results show that Life Expectancy and Minimum Wage at level 1 and GRDP at level 2 have a significant influence on district/city TPT on Java Island in 2022
References
Afifah, N., Romhadhoni, P. & Faizah. D. Z., 2018. Pengaruh Produk Domestik Regional Bruto (PDRB) Daerah terhadap Pertumbuhan Ekonomi dan Tingkat Pengangguran Terbuka di Provinsi DKI Jakarta. Jurnal Matematika Interaktif, Vol. 4, No. 2, 115–121. https://doi.org/10.24198/jmi.v14.n2.19262.113-120
Agresti, A., 2007. An Introduction to Categorical Data Analysis, Second Edition. John Wiley & Sons Inc., New Jersey.
Amalia, E. & Sari, L. Z., 2019. Analisis Spasial Untuk Mengidentifikasi Tingkat Pengangguran Terbuka Berdasarkan Kabupaten/Kota di Pulau Jawa Tahun 2017. Indonesian Journal of Statistics and Its Applications, Vol. 3, No. 3, 202–215. https://doi.org/10.29244/ijsa.v3i3.240.
Anggadini, F., 2015. Analisis Pengaruh Angka Harapan Hidup, Angka Melek Huruf, Tingkat Pengangguran Terbuka dan Pendapatan Domestik Regional Bruto Perkapita terhadap Kemiskinan Pada Kabupaten/ Kota Di Provinsi Sulawesi Tengah Tahun 2010-2013. Katalogis, Vol. 3, No. 7.
Aprilia, Z., Afendi, F. M. & Akbar, R., 2021. Penerapan Regresi Logistik Biner Multilevel terhadap Ketepatan Waktu Lulus Mahasiswa Program Magister Sekolah Pascasarjana IPB. Xplore: Journal of Statistic, Vol. 10, No. 2, 102–111. https://doi.org/10.29244/xplore.v10i2.199
BPS, 2022. Keadaan Ketenagakerjaan Indonesia Agustus 2022. BPS, Jakarta.
BPS, 2022. Tingkat Pengangguran Terbuka Menurut Provinsi (Persen). [diakses 2023 Des 10]. https://www.bps.go.id/id/statistics-table/2/NTQzIzI=/tingkat-pengangguran-terbuka--februari-2024.html.
Chikako, T. U. 2018. Multilevel Modelling of Determinants of Youth Unemployment in Urban Ethiopia: Bayesian Estimation Approach. International Journal on Data Science and Technology, Vol. 4, No. 67. https://doi.org/10.11648/j.ijdst.20180402.15.
Dodge, Y., 2008. Regression Analysis. In: The Concise Encyclopedia of Statistics. Springer, New York.
Fatmasari, Y., 2018. Pengaruh PDRB, Pendidikan, dan Pengangguran terhadap Kemiskinan di Jawa Timur Tahun 2006-2015. Jurnal Ilmiah Mahasiswa FEB, Vol. 6, No. 1.
Ghinastri, S. L. & Syafitri, W., 2024. Pengaruh Upah Minimum Kabupaten/Kota (MK) terhadap Tingkat Pengangguran Terbuka (TPT) dan Kemiskinan. Journal of Development Economic and Social Studies, Vol. 3, No. 1, 72–83. http://dx.doi.org/10.21776/jdess.2024.03.1.6
Goldstein, H., 1995. Multilevel Statistical Models, Second Edition. Arnold, London.
Hox, J. J., 2002. Multilevel Analysis: Techniques and Applications. Lawrence Erlbaum Associates Publishers, New Jersey.
Hosmer, D., Lemeshow. S. & Sturdivan, R., 2013. Applied Logistic Regression, Third Edition. John Wiley & Sons Inc., New York.
Mandasari, R., Indahwati, I. & Kurnia, A. 2018. Multilevel Panel Data Modelling for Unemployment Rate in Indonesian. International Journal of Sciences: Basic and Applied Research (IJSBAR), Vol. 40, No. 2, 99–108.
Muhdar, H. M., 2015. Potret Ketenagakerjaan, Pengangguran, dan Kemiskinan di Indonesia: Masalah dan Solusi. Jurnal Al-Buhuts, Vol. 11, No. 1, 42–66.
Pamungkas, P. A. & Suman, A., 2016. Pengaruh Upah Minimum terhadap Pengangguran dan Kemiskinan di Indonesia tahun 2011-2016. Jurnal Ilmiah Mahasiswa FEB, Vol. 5, No. 2.
Permata, R. P. & Ni’mah, R., 2023. Analisis Regresi Logistik Biner Multilevel pada Status Kemiskinan di Pulau Jawa menggunakan Algoritma MCMC Metropolis-Hasting. J Statistika: Jurnal Ilmiah Teori Dan Aplikasi Statistika, Vol. 16, No. 1, 316–327. https://doi.org/10.36456/jstat.vol16.no1.a6578
Prahasta, K. F., Isnaniah, U. N., Nurlaily, D., Nurhayati, F. & Silfiani, M., 2023. Analisis Pengaruh Umur Harapan Hidup, Harapan Lama Sekolah, Rata-rata Lama Sekolah dan Tingkat Pengangguran Terbuka terhadap Indeks Pembangunan Manusia berdasarkan Kabupaten/Kota di Pulau Kalimantan Tahun 2022. Equiva, Vol 1, No. 2
Pramaysti, L. K., 2022. Perbandingan Analisis Regresi Logistik Biner dengan Analisis Deskriminan Pada Data tingkat Pengangguran Terbuka Provinsi Jawa Barat dan Jawa Tengan tahun 2020. Skripsi. Universitas Lampung, Lampung.
Romhadhoni, P., Faizah, D. Z. & Afifah, N., 2018. Pengaruh Produk Domestik Regional Bruto (PDRB) Daerah terhadap Pertumbuhan Ekonomi dan Tingkat Pengangguran Terbuka di Provinsi DKI Jakarta. Jurnal Matematika Integratif, Vol. 14, No. 2. 115–121. https://doi.org/10.24198/jmi.v14.n2.19262.113-120
Saragih, M. T., Inayah, A. W., Nooraeni, R., Aprilio, M., Sinsyi, M. M. & Aprilia, Y. R., 2020. Penerapan Regresi Logistik Biner Multilevel pada Partisipasi Angkatan Kerja di Provinsi Jawa Tengah Tahun 2018. Eigen Mathematics Journal, Vol. 3, No. 1, 35–44. https://doi.org/10.29303/emj.v3i1.60
Seyoum, T. F., Andualem, Z. & Yalew, H.F., 2023. Insecticide-treated bed net use and associated factors among households having under-five children in East Africa: a multilevel binary logistic regression analysis. Malar J, Vol. 22, No. 10. https://doi.org/10.1186/s12936-022-04416-y
Siskawati, N., Surya, R. Z. & Sudeska, E., 2021. Pengaruh Harapan Lama Sekolah, Rata – Rata Lama Sekolah Terhadap Tingkat Pengangguran Terbuka di Kabupaten / Kota Provinsi Riau. Selodang Mayang: Jurnal Ilmiah Badan Perencanaan Pembangunan Daerah Kabupaten Indragiri Hilir, Vol. 7, No. 3, 173–177. https://doi.org/10.47521/selodangmayang.v7i3.231
Snijders, T. A. B. & Bosker, R. J., 1999. Multilevel analysis: An introduction to basic and advanced multilevel modeling. Sage Publications, Thousand Oaks.
Zeru, N. G., Tolessa, D. B., Fufa, J. A. & Fufa, B. G., 2023. Multilevel logistic regression analysis of factors associated with delivery care service utilization among childbearing women in Ethiopia. Front. Reprod. Health, Vol. 5, No. 1045964. https://doi.org/10.3389/frph.2023.1045964
Zewude, B. T., Debusho, L. K. & Diriba T. A., 2022. Multilevel logistic regression modelling to quantify variation in malaria prevalence in Ethiopia. PLoS ONE, Vol. 17, No. 9: e0273147. https://doi.org/10.1371/journal.pone.0273147
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