PENERAPAN REGRESI SPASIAL DALAM MENGIDENTIFIKASI FAKTOR FAKTOR YANG BERPENGARUH TERHADAP PENDAPATAN DAERAH DI PROVINSI JAWA BARAT MENGGUNAKAN METODE SPATIAL EROR MODEL (SEM), GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) DAN PEMETAAN BERBASIS WEBGIS
Abstract
Regional income is a very important revenue for the regional government in
supporting regional development to finance regional projects and activities. West
Java is one of the provinces in Indonesia with the largest regional income, data
from Badan Pusat Statistika of West Java Province in 2018 noted that this area has
various supporting economic factors such as a population of 48 million people, 398
tourist attractions, 6874 companies engaged in various fields business, as well as
1722 the number of hotels spread across 18 districts and 8 cities. Spatial regression
is a statistical method used to determine the relationship between response
variables and predictor variables by considering the interrelationships between
regions. Based on the results of exploration of the region with the highest regional
income in the city of Bandung with a value of 6352 million rupiah. In this study
aims to determine the regional income prediction model in West Java using the
Spatial Error Model (SEM). This is due to the high inequality in the realization of
the Regional Revenue and Expenditure Budget for each city and district in the
region. Conclusions obtained The largest regional income is in Tasikmalaya
Regency, Sukabumi Regency, Bandung Regency, Garut Regency, Bandung City,
Bogor Regency, Bekasi City, Karawang Regency and Bekasi Regency. Seen from
the identification of spatial effects on regional income there is a low-high
relationship. The most appropriate model in describing regional income in West
Java Province is the Geographically Weighted Regression (GWR) Model with an
rsquare value of 96.58%. Then the results of the modeling are classified by groups
and then create a WebGIS-based map using QGIS cloud.
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