Analisis Pengaruh Aglomerasi, Investasi, Dan TenagaKerja Terhadap Pertumbuhan Ekonomi Provinsi JawaTengah Tahun 2010-2014

• Main Authors: Yulianto, Dwi (Author), , Ir. Maulidyah Indira Hasmarini, M.S (Author)
• Format: Book
• Published: 2017.
• Subjects: Thesis; NonPeerReviewed
• Online Access: Connect to this object online
• Notes: https://eprints.ums.ac.id/53656/11/NASKAH%20PUBLIKASI-dwi.pdf; https://eprints.ums.ac.id/53656/2/HALAMAN%20DEPAN.pdf; https://eprints.ums.ac.id/53656/3/BAB%20I.pdf; https://eprints.ums.ac.id/53656/4/BAB%20II.pdf; https://eprints.ums.ac.id/53656/5/BAB%20III.pdf; https://eprints.ums.ac.id/53656/6/BAB%20IV.pdf; https://eprints.ums.ac.id/53656/7/BAB%20V.pdf; https://eprints.ums.ac.id/53656/8/DAFTAR%20PUSTAKA.pdf; https://eprints.ums.ac.id/53656/9/LAMPIRAN.pdf; https://eprints.ums.ac.id/53656/10/SURAT%20PERNYATAAN%20PUBLIKASI.pdf
• Keywords: HB Economic Theory

This study entitled "Analysis of Agglomeration, Investment and Labor Influence on Economic Growth of Central Java Province Year 2010-2014". The objective is to analyze the effect of agglomeration, investment, and labor on economic growth of Central Java Province in 2010-2014. Dependent variable is economic growth (PE), while agglomeration independent variable (AGLO), investment (INV), and labor (TK). This study uses secondary data with panel data regression analysis technique. The results show that Fixed Effect Model (FEM) is the most appropriate data panel regression model. Based on the validity test of influence or t test, agglomeration is not significant to economic growth, while investment and labor are marked positively and significantly to economic growth. Based on the F test, agglomeration, investment, and labor simultaneously or together affect economic growth. Regression output results show the coefficient of determination (R2) of 0.991831, the interpretation is the variation of economic growth variables can be explained by 99.18% by the variation of independent variables in the study while the rest of 0.82% explained by variations of variables outside the model. Keywords: Economic growth, agglomeration, investment, labor, regression of panel data.