Lia Miftakhul Janah
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PERBANDINGAN METODE GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) DAN ORDINARY LEAST SQUARE (OLS) DALAM PEMODELAN KETIMPANGAN DI PROVINSI JAWA TENGAH Lia Miftakhul Janah; Tiani Wahyu Utami
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Prosiding Seminar Nasional Pendidikan, Sains dan Teknologi
Publisher : Universitas Muhammadiyah Semarang

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Abstract

nequality is a state where there is an imbalance between each other. Inequality indicates the unevenness of development that runs in an area.In Central Java, the problem of inequality among people still exists in daily life. Geographically Weight Regression method is a method that yields model parameter estimators that have localized properties at each point or location. While OrdinaryLeast Square method is a linear regression that doesn’t have territorial element. In this study aims to modeling the inequality problem that occurred in Central Java using Geographically Weight Regression method that has the nature of localization at the point and Ordinary Least Square method. Data taken from Central Statistics Agency (BPS) 2015. Through Geographically Weight Regression method can be concluded that 2 variables effect on imbalance with α 10% is variable of Total population (0,4078) and Labor (0,9502) . While the influential OLSmethod is the Human DevelopmentIndex and Averageper-capita expendixture.  AIC value of GWRis smaller than OLS Method (93.45184<105.1492)Which is mean GWR methodbetter than OlS in modelling inequality at Central Java.Keywords: Inequality, GWR,OLS
PEMODELAN KETIMPANGAN DI PROVINSI JAWA TENGAH DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) Lia Miftakhul Janah; Widia Istiqomah; Maharani Andini
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 5, No 1 (2017): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (75.89 KB) | DOI: 10.26714/jsunimus.5.1.2017.%p

Abstract

Ketimpangan adalah keadaan dimana terjadi ketidakseimbangan antara satu dengan lainya. Ketimpangan menunjukkan ketidak meratanya pembangunan yang berjalan di suatu daerah tersebut. Di Jawa Tengah sendiri masalah ketimpangan antar masyarakat masih ada dalam kehidupan sehari hari. Metode Geographically Weight Regression (GWR)merupakan metode yang menghasilkan penaksir parameter model yang mempunyai sifat kelokalan pada masing-masing titik atau lokasi. Dalam penelitian ini bertujuan untuk memodelkan masalah ketimpangan yang terjadi di Provinsi Jawa tengah menggunakan metode Geographically Weight Regression (GWR)yang memiliki sifat kelokalan pada titik. Data yang digunakan bersumber dari Badan Pusat Statistika tahun 2015. Melalui metode Geographically Weight Regression didapatkan bahwa setiap kenaikan pada Jumlah Penduduk sebesar 1 satuan maka ketimpangan akan berkurang sesbesar 1.476. Setiap kenaikan 1 satuan pada Jumlah tenaga Kerja maka ketimpangan akan naik sebesar 1.009. Nilai AIC dari GWRlebih kecil dibandingkan OLS yang berarti metode GWR lebih baik dibandingkan metode OLS dalam pemodelan masalah ketimpangan di Provinsi Jawa Tengah.Kata Kunci: Ketimpangan, GWR, OLS
GEOGRAPHICALLY WEIGHT REGRESSION APPLICATIONS FOR SPATIAL ANALYSIS OF INEQUALITY IN CENTRAL JAVA Lia Miftakhul Janah; M. Saifudin Nur; Tiani Wahyu Utami
PROSIDING SEMINAR NASIONAL & INTERNASIONAL 2017: Proceeding 3rd ISET 2017 | International Seminar on Educational Technology 3rd 2017
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (657.247 KB)

Abstract

Inequality is a state where there is an imbalance between each other. Inequality indicates the unevenness ofdevelopment that runs in an area. In Central Java, the problem of inequality among people still exists in daily life.Geographically Weight Regression method is a method that yields model parameter estimators that have localizedproperties at each point or location. In this study aims to modeling the inequality problem that occurred in CentralJava using Geographically Weight Regression method that has the nature of localization at the point. Data takenfrom Central Statistics Agency (BPS) 2015. Through Geographically Weight Regression method can beconcluded that with OLS method got 2 variables effect on imbalance wit h α 10% is variable of HDI  (IPM) andPDRB. While the influential GWR method is the number of population and the amount of labor. While goodnessof fit test showed there is no difference between GWR model and OLS model or in other words there is no spatialeffect in the imbalance analysis in Central Java Province (0.4976 <0.1).Keywords: inequality, GWR,Spatial