Komunikasi Fisika Indonesia
Vol 18, No 1 (2021)

PREDIKSI KADAR PARTICULATE MATTER (PM10) MENGGUNAKAN JARINGAN SYARAF TIRUAN DI KOTA PEKANBARU

Wima Puspita (Universitas Riau)
Defrianto Defrianto (Universitas Riau)
Yan Soerbakti (Universitas Riau)

Article Info

Publish Date
31 Mar 2021

Abstract

This aims of this study is to predict particulate matter (PM10) levels in Pekanbaru using back propagation artificial neural networks (ANN) based on weather factors. The data used in the form of data from 2014 – 2017 as training data and 2018 data as test data. The architecture proposed is composed of 5 – 5 – 1 neurons and uses the logig-logsig-purelin functions. The training process produces a traincgb with a small MSE value and in the process of testing the PM10 prediction compared to BMKG data has an average error of 26.9062%.

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Journal Info
Komunikasi Fisika Indonesia
Website

Abbrev

JKFI

Publisher

Universitas Riau

Subject

Earth & Planetary Sciences Electrical & Electronics Engineering Energy Materials Science & Nanotechnology Physics

Description

KFI mempublikasikan artikel hasil penelitian dan review pada bidang fisika, namun tidak terbatas, yang meliputi fisika murni, geofisika, plasma, optik dan fotonik, instrumentasi, dan elektronika, dan fisika terapan (aplikasi ...