Geographically Weighted Panel Regression Modelling of Human Development Index Data in East Kalimantan Province in 2017-2020
| Main Authors: | Ananda, Ni Made Shantia , Suyitno, Suyitno, Siringoringo, Meiliyani |
|---|---|
| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
Department of Mathematics, Hasanuddin University
, 2023
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| Subjects: | |
| Online Access: |
http://journal.unhas.ac.id/index.php/jmsk/article/view/23775 http://journal.unhas.ac.id/index.php/jmsk/article/view/23775/9156 |
Daftar Isi:
- Geographically Weighted Panel Regression (GWPR) model is a panel regression model applied on spatial data. This research applied Fixed Effect Model (FEM) on panel regression as the global model and GWPR as the local model for Human Development Index (HDI) regencies/municipalities in East Kalimantan Province data over the years 2017-2020. The aim of this research is to obtain the GWPR model of HDI data, as well as to acquire factors that influence it. The parameter of GWPR model was estimated on each observation location using the Weighted Least Square (WLS) method, namely Ordinary Least Square (OLS) with addition of spatial weighting. The spatial weighting on GWPR model was calculated using fixed bisquare, fixed tricube, adaptive bisquare and adaptive tricube. After the selection process, the optimum weighting function is adaptive tricube which provides a minimum Cross Validation (CV) value of 5.1419. Based on GWPR parameter testing, factors that affect HDI are local and diverse in each 10 regencies/municipalities in East Kalimantan Province. These factors are the labor force participation rate, number of health facilities, Gini ratio, population growth rate, open unemployment rate, poverty gap index and percentage of food expenditure. The coefficient of determination of the GWPR model obtains a value of 94.36% with the RMSE value of 0.1221.
- Model Geographically Weighted Panel Regression (GWPR) merupakan model regresi panel yang diterapkan pada data spasial. Penelitian ini menerapkan Fixed Effect Model (FEM) pada regresi panel sebagai model global dan GWPR sebagai model lokal untuk data Indeks Pembangunan Manusia (IPM) kabupaten/kota di Provinsi Kalimantan Timur tahun 2017-2020. Penelitian ini bertujuan untuk memperoleh model GWPR untuk data IPM, serta faktor-faktor yang mempengaruhinya. Parameter model GWPR diestimasi pada setiap lokasi pengamatan menggunakan metode Weighted Least Square (WLS) yaitu Ordinary Least Square (OLS) dengan penambahan pembobotan spasial. Pembobotan spasial pada model GWPR dihitung menggunakan fungsi pembobot fixed bisquare, fixed tricube, adaptive bisquare dan adaptive tricube. Setelah proses penyeleksian, fungsi pembobot optimum adalah adaptive tricube yang memberikan nilai Cross Validation (CV) minimum sebesar 5,1419. Berdasarkan pengujian parameter model GWPR, faktor-faktor yang mempengaruhi IPM bersifat lokal dan beragam di setiap 10 kabupaten/kota di Provinsi Kalimantan Timur. Faktor-faktor tersebut adalah tingkat partisipasi angkatan kerja, jumlah fasilitas kesehatan, Gini ratio, laju pertumbuhan penduduk, tingkat pengangguran terbuka, indeks kedalaman kemiskinan dan persentase pengeluaran per kapita kelompok makanan. Koefisien determinasi model GWPR sebesar 94,36% dengan nilai RMSE sebesar 0,1221.