Klasifikasi Ketinggian Gelombang Laut Perairan Masalembu Berdasarkan Hasil Prediksi Parameter Meteorologi Maritim Menggunakan Metode Backpropagation


  • Nugroho Wahyu W. UIN Sunan Ampel Surabaya
  • Dian C. Rini Novitasari UIN Sunan Ampel Surabaya
  • Ady Hermanto BMKG Perak II


Classification; Prediction; Backpropagation; MAPE; Confusion Matrix


Indonesia is a maritime country in other words a lot of daily activities and people's economy depends on competition. To support the smoothness of all activities in the field required weather forecasting, especially for waves. One example of an archipelago that relies on wave height forecasts is the island of Masalembu, which is related to the island which discusses all daily activities and repairs carried out in the waters. Therefore this study was conducted to classify wave heights on Masalembu ships including hazard classes or not. This study uses the Backpropagation method to predict meteorological parameters such as wave height, wind speed, and current speed. The results of the parameter prediction get MAPE 1.4743 with the best network architecture from the learning level of 0.3, then these results are used for the classification process with calculations using the confusion matrix. This study obtained results reaching 99.03%.


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