ANALISIS SPASIAL UNTUK MENGIDENTIFIKASI TINGKAT PENGANGGURAN TERBUKA BERDASARKAN KABUPATEN/KOTA DI PULAU JAWA TAHUN 2017

  • Eka Amalia BPS Kabupaten Kolaka Utara, Indonesia
  • Liza Kurnia Sari Politeknik Statistika STIS, Indonesia
Keywords: geographically weighted regression, open unemployment rate, spatial

Abstract

Unemployment is one of the economic problems faced by many countries. In Indonesia, the total workforce has reached 128.06 million and 7.04 million people are unemployed. The indicator to measure unemployment is open unemployment rate (TPT). Java Island becomes the island with the highest TPT, which is 4.04 million people, equivalent to 63.08 percent. The regions that have high TPT rates tend to be in the western region of Java, while the eastern region of Java is moderate. This is an initial allegation of regional influence so spatial analysis needs to be carried out. On the other hand, not many studies have included territorial effects. This study aims to spatially identify the influence of human development index (IPM), labor force particapation rate (TPAK), minimum wage and the dependency ratio on the number of TPT in Java in 2017 with the geographically weighted regression (GWR) method. The results of this study indicate that there are differences in the influence of IPM, TPAK, minimum wage and the dependency ratio on TPT in each area in Java. The most significant independent variables and have a positive relationship are minimum wage. This research also shows that GWR is suitable to be applied in modeling the number of TPT regencies /cities in Java Island in 2017. The results of this study can be used by the government in determining the right policy by looking at regional aspects in overcoming unemployment.

References

Burhanudin, M. (2016). Pengaruh produk domestik regional bruto (PDRB), upah minimum kabupaten/kota (UMK), dan indeks pembangunan manusia (IPM) terhadap tingkat pengangguran di Provinsi Banten periode 2008-2013 [skripsi]. Jakarta: UIN Syarif Hidayatullah.

Fotheringham, A.S., Brunsdon, C., and Charlton, M. (2003). Geographically weighted regression: the analysis of spatially varying relationships. Chichester, UK: John Wiley & Sons.

Hajji, M.S., and Nugroho, S. (2013). Analisis PDRB, inflasi, upah minimum provinsi, dan angka melek huruf terhadap tingkat pengangguran terbuka di Provinsi Jawa Tengah tahun 1990-2011. Diponegoro Journal of Economics, 2(3): 36-45.

Ilahi, R., Syamsuddin, M., and Suparman, Y. (2014). Model spasial durbin dengan efek tetap untuk tingkat pengangguran terbuka di Provinsi Kepulauan Bangka Belitung, in: Prosiding Seminar Nasional Statistika, Departemen Statistika FMIPA Universitas Padjadjaran. pp. 424–436.

Mulyani, F. (2017). Determinan kemiskinan di kawasan timur indonesia (KTI) tahun 2015 menggunakan metode geographically weighted regression (GWR) [skripsi]. STIS, Jakarta.

Nakaya, T. (2012). GWR4 user manual. WWW document.

Putro, A.S., and Setiawan, A.H. (2013). Analisis pengaruh produk domestik regional bruto, tingkat upah minimum kota, tingkat inflasi dan beban/tanggungan penduduk terhadap pengangguran terbuka di Kota Magelang periode tahun 1990–2010. Diponegoro Journal of Economics, 2(3):12–25.

Sukirno, S. (2010). Teori pengantar makroekonomi edisi ketiga. Jakarta: PT. Raja Grafindo Pesada.

Wijaya, A.F.H. (2018). Analisis faktor-faktor yang mempengaruhi tingkat pengangguran terbuka (TPT) di Provinsi Aceh dengan regresi nonparametrik spline truncated [skripsi]. Surabaya: Institut Teknologi Sepuluh Nopember.

Published
2019-10-31
Section
Articles