Maulita, Niken (2024) Pemodelan PDRB Sektor Industri Pengolahan dan Sektor Perdagangan Besar dan Eceran di Jawa Timur dengan Regresi Spasial. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Perekonomian merupakan salah satu indikator kemajuan suatu negara. Produk Domestik Regional Bruto (PDRB) merupakan salah satu indikator ekonomi makro yang dapat mengukur kegiatan ekonomi di suatu daerah. PDRB dapat mencerminkan potensi perekonomian daerah, nilai PDRB ialah total nilai tambah yang dihasilkan oleh unit-unit produksi yang dihasilkan di wilayah tersebut. Kasus PDRB kemungkinan dipengaruhi oleh lokasi atau kondisi geografis wilayah sehingga analisis yang digunakan harus mempertimbangkan data ruang atau spasial sehingga penelitian ini menggunakan metode regresi spasial. Penelitian ini menggunakan PDRB di dua sektor di Provinsi Jawa Timur yaitu Sektor Industri Pengolahan dan Sektor Perdagangan Besar dan Eceran. PDRB merupakan output (barang dan jasa) yang memerlukan input proses produksi yaitu modal dan tenaga kerja. Variabel prediktor yang digunakan adalah Investasi Sektoral, Jumlah Tenaga Kerja Sektoral, Upah Riil Sektoral dan Rata-rata Lama Sekolah dengan data cross section pada tahun 2021. Hasil pemodelan PDRB pada Sektor Industri Pengolahan adalah model SAR dengan pembobot Customize sedangkan pada PDRB Sektor Perdagangan Besar dan Eceran adalah model SAR dengan pembobot Queen Contiguity.
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The economy is an indicator of the progress of the country. Gross Regional Domestic Product (GRDP) is a macroeconomic indicator that can measure economic activity in an area. GRDP can reflect regional economic potential, the GRDP value is the total added value produced by production units produced in the region. The GRDP case is likely to be influenced by the location or geographical conditions of the region so that the analysis used must consider space or spatial data, so this research uses the spatial regression method. This research uses GRDP in two sectors in East Java Province including the Processing Industry Sector and Wholesale and Retail Trade Sector. GRDP is output (goods and services) that requires production process input, namely capital and labor. The predictor variables used are Sectoral Investment, Number of Sectoral Workers, Sectoral Real Wages and Average Years of Schooling with cross section data in 2021. The results of the GRDP modeling in the Processing Industry Sector are the SAR model with Customize weighting, while the GRDP for the Wholesale and Retail Trade Sector is the SAR model with Queen Contiguity weighting.
Item Type: | Thesis (Other) |
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Uncontrolled Keywords: | GRDP, Spatial Regression, Processing Industry Sector, Wholesale and Retail Trade Sector, PDRB, Regresi Spasial, Sektor Industri Pengolahan, Sektor Perdagangan Besar dan Eceran |
Subjects: | H Social Sciences > HA Statistics H Social Sciences > HA Statistics > HA30.6 Spatial analysis H Social Sciences > HB Economic Theory Q Science Q Science > Q Science (General) Q Science > QA Mathematics |
Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
Depositing User: | Niken Maulita |
Date Deposited: | 15 Aug 2024 07:06 |
Last Modified: | 15 Aug 2024 07:06 |
URI: | http://repository.its.ac.id/id/eprint/114692 |
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