Penerapan Model Mixed Geographically Weighted Regression dengan Fungsi Pembobot Adaptive Tricube pada IPM 30 Kabupaten/Kota di Provinsi Kalimantan Timur, Kalimantan Tengah dan Kalimantan Selatan Tahun 2016

  • Ranita Nur Safitri Laboratorium Statistika Terapan FMIPA Universitas Mulawarman
  • Suyitno Suyitno Laboratorium Statistika Terapan FMIPA Universitas Mulawarman
  • Memi Nor Hayati Laboratorium Statistika Terapan FMIPA Universitas Mulawarman

Abstract

Mixed Geographically Weighted Regression (MGWR) model is a Geographically Weighted Regression (GWR) model which has global (equal value) and local (inequal value) parameters at every different observation location. The goal of this study is to obtain MGWR model of the Human Development Index (HDI) data and find out significant factors influencing the HDI in each district (city) East Kalimantan, Central Kalimantan and South Kalimantan province in 2016. Parameter estimation method is conducted in two stages namely local parameter estimation and global parameter estimation. Local parameter estimation method is Maximum Likelihood Estimation (MLE), with spatial weighting is calculated by  adaptive tricube weighting function and optimum bandwidth determination uses the Akaike Information Criteria (AIC). Global parameter estimation method is Ordinary Least Square (OLS). Based on the result of MGWR parameter testing, it was concluded that the school enrollment rates (SMP) and poor people percentage affected the HDI of 30 districts (cities) in East Kalimantan, Central Kalimantan and South Kalimantan. Meanwhile the population density affected the HDI of two districts namely HDI of Samarinda and Bontang.

Published
2021-01-19
How to Cite
SAFITRI, Ranita Nur; SUYITNO, Suyitno; HAYATI, Memi Nor. Penerapan Model Mixed Geographically Weighted Regression dengan Fungsi Pembobot Adaptive Tricube pada IPM 30 Kabupaten/Kota di Provinsi Kalimantan Timur, Kalimantan Tengah dan Kalimantan Selatan Tahun 2016. JURNAL EKSPONENSIAL, [S.l.], v. 11, n. 2, p. 107-116, jan. 2021. ISSN 2085-7829. Available at: <http://jurnal.fmipa.unmul.ac.id/index.php/exponensial/article/view/651>. Date accessed: 23 june 2021.