PREDIKSI KECEPATAN ANGIN MENGGUNAKAN MODEL ARTIFICIAL NEURAL NETWORK BERBASIS ADABOOST - Abdul Syukur; Catur Supriyanto; Akhmad Khanif Zyen (Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro, 2017)
Prediction is an attempt to predict the future by examining the past. This prediction consists of the bias estimation of the magnitude of future several variables, such as sales, on the basis of knowledge of the past, present, and experience. Adaboost is one of the optimization algorithm which can improve the accuracy of a predictive value. Previous research examines the exchange rate prediction of wind speed using back propagation Artificial Neural Network algorithm. The purpose of this study is intended to improve the accuracy of prediction of wind speed previously predicted using Artificial Neural Network Backpropagation algorithm then improved the prediction accuracy using adaboost algorithm during the process of training and added back propagation Artificial Neural Network algorithm in the learning process.The results showed that the prediction accuracy of the wind speed values previously predicted using Artificial Neural Network back propagation algorithm with an accuracy of prediction error at sample time per 10 minute predictions of 0.31576596 managed to reduce the value of the accuracy of the prediction error using adaboost algorithm during training and coupled Artificial Neural Network algorithm Backpropagation learning process with an accuracy of prediction error amounting to 0.15945762.