Model Hidrologi Runtun Waktu Untuk Peramalan Debit Sungai Menggunakan Metode Artifical Neural Network (ANN) (Studi Kasus : Sub DAS Siak Hulu) - fadly, Rendy; Suprayogi, Imam; Fauzi, Manyuk (Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains, 2015)
ANN method is a soft computing method that can predict streamflow. predict streamflow is needed at the present time, one of which is for early warning flood. Judging from the success of the research is the application of ANN method, it is necessary to prove the performance of the ANN method to predict streamflow in Siak Hulu Sub-Watershed. The data used for the development of ANN model predict streamflow in Siak Hulu Sub-Watershed is derived from the historical recording of data in Automatic Water Level Record (AWLR) station of Pantai Cermin from 2002 to 2012 (except 2007). ANN model development consists of 4 forecasting scheme is then compared to obtain the best model. In each of the schemes carried out the training process, testing, and validation. The algorithm used in the development of ANN model is backpropagation algorithm. The results obtained in this study indicate that the performance of the ANN model that has been made to produce the value of the test statistic parameters of the correlation coefficient (R) categorized as a very strong correlation. The best forecasting scheme obtainedthat the forecasting scheme for one day to the next (Qt+1) which resulted in a correlation coefficient (R) is 0.94903.Keywords: forecasting streamflow, ANN, Siak Hulu sub-watershed.