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M. Afif Amirillah
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Decision Sciences, Operations Research & Management

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PEMODELAN GENERAL REGRESSION NEURAL NETWORK UNTUK PREDIKSI TINGKAT PENCEMARAN UDARA KOTA SEMARANG Warsito, Budi; Rusgiyono, Agus; Amirillah, M. Afif
MEDIA STATISTIKA Vol 1, No 1 (2008): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (86.16 KB) | DOI: 10.14710/medstat.1.1.43-51

Abstract

This paper is discuss about General Regression Neural Network (GRNN) modelling to predict time series data, i.e. the air pollution rate in Semarang City comprises the floating dust, carbon monoxide (CO) and nitrogen monoxide (NO). The GRNN model have four processing layer that are input layer, pattern layer, summation layer and output layer. The input variable is determined by the ARIMA model. The result of GRNN modelling shows that the network have a good performance both at predict in sample and predict out of sample, that can be seen from the mean square error.   Keywords: GRNN, predict, air pollution  
Co-Authors Agus Rusgiyono Budi Warsito