Analisis Faktor-Faktor yang Memengaruhi Angka Partisipasi Kasar SMA/Sederajat di Indonesia Menggunakan Regresi Ridge

Utriweni Mukhaiyar; Ferdy Rontos; Kurnia Handoko; Salma Kardiyanti

doi:10.34312/euler.v10i2.15903

Analisis Faktor-Faktor yang Memengaruhi Angka Partisipasi Kasar SMA/Sederajat di Indonesia Menggunakan Regresi Ridge

Utriweni Mukhaiyar, Ferdy Rontos, Kurnia Handoko, Salma Kardiyanti

Abstract

One indicator of education in Indonesia is the gross enrollment ratio (GER). Based on data from Statistics Indonesia, the GER at the senior high school level in Indonesia is still low compared to the GER at primary and junior high schools. Summarizing the findings of prior studies, the factors affecting GER include the number of schools, percentage of poor population, education budget, and student-teacher ratio. Therefore, this study aims to examine the variables that affect GER in Indonesian senior high schools. Since multicollinearity between the predictor variables was identified, ridge regression was employed. This study found that the number of senior high schools, the percentage of the poor population, and the education budget simultaneously had a significant effect and contributed 71.39% to the GER at the senior high school level in Indonesia. It is remarkable to observe that, partially, the number of senior high schools, the percentage of poor people, and the education budget had no direct effect on the GER. Additionally, there was a positive correlation between the variables and GER. The number of senior high schools and the education budget have a favorable impact. In contrast, the percentage of poor people has a negative effect on GER. Meanwhile, the student-teacher ratio does not have a linear relationship with the GER at the senior high school level in Indonesia.

Keywords

Gross Enrollment Ratio; Multicollinearity; Ridge Regression

Full Text:

PDF

References

Badan Pusat Statistik, “Sosial dan Kependudukan: Pendidikan,” 2021. [Online]. Available: https://www.bps.go.id/subject/28/pendidikan.html#subjekViewTab1. [Accessed: 16-May-2022].

Kemdikbud, “APK-APM,” 2021. [Online]. Available: https://apkapm.data.kemdikbud.go.id/. [Accessed: 16-May-2022].

R. T. Rutfiana, and B. Hayati, “Analisis Pengaruh Pemberian Dana Pendidikan Bantuan Operasional Sekolah Terhadap Angka Partisipasi Kasar (APK) di Kabupaten/Kota Provinsi Jawa Tengah Tahun 2015-2017,” Diponegoro Journal of Economics., vol. 9, no. 2, pp. 41–55, Jul. 2021.

N. A. Lestari, and A. Adji, “Analisis Faktor-faktor yang Memengaruhi Angka Partisipasi Sekolah serta Angka Putus Sekolah Tingkat Sekolah Dasar dan Sekolah Menengah Pertama: Data Panel 33 Provinsi di Indonesia tahun 2006 hingga 2011,” Universitas Gadjah Mada, Yogyakarta, 2014.

P. Karini, “Pengaruh Tingkat Kemiskinan Terhadap Angka Partisipasi Sekolah Usia 16-18 Tahun di Provinsi Kepulauan Bangka Belitung,” Al-Ishlah: Jurnal Pendidikan., vol. 6, no. 3, pp. 103–115, 2018.

S. Habibah, Y. P. Putra, and Y. M. Putra, “Faktor-faktor yang Memengaruhi Angka Partisipasi Perguruan Tinggi pada 32 Provinsi di Indonesia Tahun 2013-2016,” Jurnal Anggaran dan Keuangan Negara Indonesia., vol. 10, no. 1, pp. 15–34, Jun. 2019.

G.K. Uyanik and N. Güler, “ A Study on Multiple Linear Regression Analysis,” Procedia-Social and Behavioral Sciences., vol. 106, pp. 234–240, 2013.

B. Nugraha, Pengembangan Uji Statistik: Implementasi Metode Regresi Linier Berganda dengan Pertimbangan Uji Asumsi Klasik, Sukoharjo: Pradina Pustaka, 2022.

J. H. Kim, “Multicollinearity and Misleading Statistical Results,” Korean Journal of Anesthesiology., vol. 72, no. 6, pp. 558–569, Jul. 2019.

M. H. Kutner, C. J. Nachtsheim, J. Neter, and W. Li, Applied Linier Statistical Model, 5 Edition. New York: McGraw-Hill, 2004.

B. Angelica, D. Gunawan, J. Christella, Y. Chandera, and R. A. Rachman “The Effect of Related Party Transactions on the Perfomance of Indonesian Listed Companies,” Jurnal Manajemen Teknologi., vol. 20, no. 1, pp. 21–39, 2021.

R. E. Walpole and R. H. Myers, Ilmu Peluang dan Statistik untuk Insinyur dan Ilmuan, Terjemahan Edisi 4. Bandung: ITB Press, 1995.

I. Nurdin, S. Sugiman, and S. Sunarmi, “Penerapan Kombinasi Metode Ridge Regression (RR) dan Metode Generalized Least Sruare (GLS) untuk Mengatasi Masalah Multikolinearitas dan Autokorelasi,” Indonesia Journal of Mathematics and Natural Sciences., vol. 41, no. 1, pp. 58–68, Apr. 2018.

T. L. Wasilaine, M. W. Talakua, and Y. A. Lesnussa, “Model Regresi Ridge untuk Mengatasi Model Regresi Linier Berganda yang Mengandung Multikolinearitas,” Barekeng: J. Il. Mat. & Ter., vol. 8, no. 1, pp. 31–37, Mar. 2014.

W. Madelhall and T. Sincich, A Second Course in Statistics Regression Analysis, 7 Edition. Boston: Pearson, 2012.

D. T. Gujarati, Basic Econometrics, 4 Edition. New York: McGraw-Hill, 2003.

D. A. Karim, Y. Adisasmita, and R. Lutan, “Hubungan Antara Motivasi Berprestasi dan Kemampuan Gerak dengan Hasil Belajar Keterampilan Teknik Dasar Hoki Mahasiswa TPB-ITB,” Jurnal Sains Keolahragaan dan Kesehatan., vol. 1, no. 1, pp. 13–16, Jun. 2016.

DOI: https://doi.org/10.34312/euler.v10i2.15903