Analisis Faktor yang Mempengaruhi Angka Buta Huruf Melalui Geographically Weighted Regression: Studi Kasus Propinsi Jawa Timur

Authors

  • Andiyono Andiyono Bina Nusantara University
  • Rokhana Dwi Bekti Bina Nusantara University
  • Edy Irwansyah Bina Nusantara University

DOI:

https://doi.org/10.21512/comtech.v4i1.2788

Keywords:

rate of illiteracy, ICT, Geographically Weighted Regression (GWR)

Abstract

Analysis of factors that influence the rate of illiteracy can provide important information for education. One such factor is the development of information and communication technology (ICT). Characteristics of illiteracy in East Java showes a spatial pattern. Therefore, to obtain the influencing factors Geographically Weighted Regression spatial modeling (GWR) is utilized. Modeling results indicate that the factors that influence the rate of illiteracy in every location are different. In general, factors influencing literacy rate is the percentage of households which have mobile phone and the percentage of households which access the internet at home.

 

Dimensions

Plum Analytics

References

Abdullah, Dahlan. (2012). Potensi Teknologi Informasi dan Komunikasi dalam Peningkatan Mutu Pembelajaran di Kelas. Diakses dari http://id.pdfsb.com/readonline/624656486541683758335a3443413d3d-585527.

Badan Pusat Statistik. (2009). Survey Sosial Ekonomi Nasional 2009. Jakarta: Badan Pusat Statistik.

Firmansyah. (2011). Pemodelan dan Pemetaan Angka Buta Huruf Provinsi Jawa Timur dengan Pendekatan Regresi Spasial. Surabaya: Institut Teknologi Sepuluh Nopember.

Fotheringham, A. S., Brunsdon, C., Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Newcastle: University of Newcastle.

Hermana. (2012). Teknologi Informasi dan Komunikasi di Negara-negara Asia: Hubungannya dengan Variabel Ekonomi Makro dan Pengembangan Sumber Daya Manusia. Depok: Universitas Gunadarma.

Putra, W. M. (2008). Analisa Hubungan Kondisi Sektor Ekonomi dan Pendidikan Terhadap Angka Kemiskinan di Jawa Timur menggunakan Metode Geographically Weighted Regression. Surabaya: Institut Teknologi Sepuluh Nopember.

Tobler. (2010). Perspectives on Spatial Data Analysis. CA: Santa Barbara.

Downloads

Published

2013-06-30

Issue

Section

Articles
Abstract 617  .
PDF downloaded 3136  .