Penaksiran Parameter Model Mixed Geographically Weighted Regression (MGWR) Data Indeks Pembangunan Manusia di Kalimantan Tahun 2016

  • Mita Asti Wulandari Laboratorium Statistika Terapan FMIPA Universitas Mulawarman
  • Suyitno Suyitno Laboratorium Statistika Terapan FMIPA Universitas Mulawarman
  • Wasono Wasono Laboratorium Matematika Komputasi FMIPA Universitas Mulawarman

Abstract

Mixed Geographical Regression (MGWR) model is a combination of global linear regression model and GWR model. Some MGWR parameters are global (the same value) and the other parameters are local (different values) ​​at each observation location. The purpose of this study is to obtain MGWR model for every District’s HDI and to obtain the factors that significantly influence District HDI in East Kalimantan, Central Kalimantan and South Kalimantan Provinces. Estimating parameters for global parameters use Ordinary Least Square (OLS) method. Estimating parameters for local parameters use Weighted Least Square (WLS) method, where weighting spatial is determined by using gaussian adaptive function. Based on the result of MGWR parameters testing, it was concluded that the school enrollment rates (SMP) affected the HDI of all districs in East Kalimantan, Central Kalimantan and South Kalimantan provinces. The population density and the percentage of poor people influence locally to HDI.

Published
2020-02-01
How to Cite
WULANDARI, Mita Asti; SUYITNO, Suyitno; WASONO, Wasono. Penaksiran Parameter Model Mixed Geographically Weighted Regression (MGWR) Data Indeks Pembangunan Manusia di Kalimantan Tahun 2016. JURNAL EKSPONENSIAL, [S.l.], v. 10, n. 2, p. 183-192, feb. 2020. ISSN 2085-7829. Available at: <http://jurnal.fmipa.unmul.ac.id/index.php/exponensial/article/view/577>. Date accessed: 19 sep. 2020.