# ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI UPAH MINIMUM KABUPATEN/KOTA DI PROVINSI JAWA TENGAH MENGGUNAKAN MODEL SPATIAL AUTOREGRESSIVE (SAR)

MERDEKAWATY, RAHMAH (2016) ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI UPAH MINIMUM KABUPATEN/KOTA DI PROVINSI JAWA TENGAH MENGGUNAKAN MODEL SPATIAL AUTOREGRESSIVE (SAR). Undergraduate thesis, Fakultas Sains dan Matematika.

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## Abstract

Spatial regression is the result of the development of linear regression method, wherein the location or spatial aspects of the analyzed data are also must be considered. The phenomenon that includes spatial data of which is the deployment of a minimum wage. Minimum Wages District/City is a minimum standard that is used by employers to provide wages to employees in its business environment on a district/city in any given year. Minimum Wages District/City is determined by considering the welfare of workers and the state of the local economy. Factors in worker welfare such as Worth Living Needs and the Consumer Price Index (CPI), while one important indicator to determine the economic conditions in the region within a certain time period is Gross Domestic Product (GDP). Modeling the influence of these factors can be determined by using multiple linear regression and spatial regression. Based on the data processing result, there is a spatial dependence in the Minimum Wages District/City variable in Central Java, so Spatial Autoregressive (SAR) method is used in this study. Variables that significantly affect the UMK in Central Java through multiple linear regression method and SAR is the Worth Living Needs (X1) and CPI (X2). The SAR model generates the value of R2 at 72.269% and AIC at 66.393, better than the multiple linear regression model that generates the value of R2 at 68% and AIC at 68.482. Keywords : Minimum Wages District/City, Worth Living Needs, CPI, GDP, multiple linear regression, spatial dependence, Spatial Autoregressive

Item Type: Thesis (Undergraduate) H Social Sciences > HA Statistics Faculty of Science and Mathematics > Department of Statistics 55016 INVALID USER 25 Jul 2017 09:07 25 Jul 2017 09:07

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