Analisis Faktor-Faktor yang Mempengaruhi Tingkat Pengangguran Terbuka di Sumatera Menggunakan Metode Multivariate Adaptive Regression Spline (MARS)
Abstract
bstract— Open Unemployment Rate (OUR) is defined as the percentage ratio of the number of open unemployment to the total labor force. In 2018, for 5 provinces in Sumatra, those are the provinces of Riau Islands, Aceh, Riau, North Sumatra and West Sumatra, the OUR value was relatively high and exceeded the OUR value in Indonesia, which was 5.34 percent. This study aims to look at the significant factors that influence OUR in Sumatra in 2018 at the best model obtained with research data in the form of secondary data obtained from the BPS-Statistics and analyzed using the Multivariate Adaptive Regression Spline (MARS) method. The best model obtained is the result of a combination of BF= 28, MI= 2, MO= 4 with the Generalized Cross Validation (GCV) value of 0,09413 as the minimum GCV value and the factors that influence the OUR, those are the independent variables X1, X2, X4, X6, and X7 with R 2 adj of 81.4 percent and factors that did not affect the independent variable were the number of households (X3) and the average expenditure per capita a month for food (X5).
Keywords— open unemployment rate, MARS, GCV.
Full Text:
PDFReferences
Aryanti, H. G dkk. (2014). Ekonomi: Peminatan Ilmu-Ilmu
Sosial . Klaten : Intan Pariwara.
Badan Pusat Statistik. (2019). Statistik Indonesia Tahun 2019.
Jakarta Pusat: Badan Pusat Statistik.
Badan Pusat Statistik. (2011). Ketenagakerjaan Penduduk
Indonesia. Jakarta: BPS
Wardani,T.J., dan Arnellis. 2019. Faktor-faktor yang
Mempengaruhi Ketidakmerataan Jumlah Penduduk di Indonesia
Menggunakan Analisis Faktor. UNPjoMath Vol.2, No.4,
ISSN:977 235516589.
Friedman, J. H. (1991). Multivariate Adaptive Regression Splines.
The Annals of Statistics. Vol. 19, hal.1-141.
Sari, R.S. (2012). Pemodelan Pengangguran Terbuka di Jawa
Timur dengan Menggunakan Pendekatan Regresi Spline
Multivariabel, Jurnal Sains dan Seni ITS,Vol 1, No.1,ISSN:2301928X
Nasuha, F. (2016). “Pemodelan Tingkat Pengangguran Terbuka
di Kabupaten/Kota Provinsi Jawa Tengah dengan Pendekatan
Multivariate Adaptive Regression Splines (MARS)”, Skripsi, 78
hal. Institut Teknologi Sepuluh Nopember ,Surabaya, Indonesia.
Badan Pusat Statistik Provinsi Aceh. (2019). Provinsi Aceh dalam
Angka 2019. Banda Aceh : Badan Pusat Statistik.
Badan Pusat Statistik Provinsi Kepulauan Riau. (2019). Provinsi
Kepulauan Riau dalam Angka 2019. Tanjungpinang : Badan
Pusat Statistik.
Badan Pusat Statistik Provinsi Riau. (2019). Provinsi Riau dalam
Angka 2019. Pekanbaru : Badan Pusat Statistik.
Badan Pusat Statistik Provinsi Sumatera Barat. (2019). Provinsi
Sumatera Barat dalam Angka 2019. Padang : Badan Pusat
Statistik.
Badan Pusat Statistik Provinsi Sumatera Utara. (2019). Provinsi
Sumatera Utara dalam Angka 2019. Medan : Badan Pusat
Statistik.
DOI: http://dx.doi.org/10.24036/unpjomath.v5i4.11097