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Muhammad Arrafi Irsyad
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Engineering

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Model Peramalan Pasang Surut Menggunakan Pendekatan Artificial Neural Network (ANN) Muhammad Arrafi Irsyad; Andy Hendri; Imam Suprayogi
Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Vol 6 (2019): Edisi 1 Januari s/d Juni 2019
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains

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Abstract

Previous researchers have much success using the model Artificial Neural Network (ANN) as a forecasting model for hydrological analysis. Reliability of ANN models need to be tested, especially to farecast of the tidal. In this research, Adaptive Neuro Fuzzy Inference System (ANFIS) models which built using data tidal observations in Tanjung Buton (2004). The result of tidal forecasting by using ANN models show excellent results with value the test statistic parameters of the correlation coefficient (R) more than 0.8774 that is in category of very strong correlation, statistic parameters of Root Mean Square Error (RMSE) 0.4362 m, and the test parameters of the average valuation relative error by 11.57%. Keywords: Tidal, Artificial Neural Network, Backpropagation, Tanjung Buton
Co-Authors Andy Hendri, MT, Andy Imam Suprayogi