PREDIKSI KADAR PARTICULATE MATTER (PM10) MENGGUNAKAN JARINGAN SYARAF TIRUAN DI KOTA PEKANBARU - Wima Puspita; Defrianto Defrianto; Yan Soerbakti (Universitas Riau, 2021)
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%.