IMPLEMENTASI BACKPROPAGATION NEURAL NETWORK DALAM PRAKIRAAN CUACA DI DAERAH BALI SELATAN
ABSTRACT: Weather information
has an important role in human life in various fields, such as agriculture marine,
and aviation. The accurate weather forecasts are needed in order to improve the
performance f various fields. In this study, use artificial neural network
method with backpropagation learning algorithm to create a model of weather
forecasting in the area of South Bali. The aim of this study is to determine
the effect of the number of neurons in the hidden layer and to determine the
level of accuracy of the method of artificial neural network with
backpropagation learning algorithm in weather forecast models. Weather forecast
models in this study use input of the factors that influence the weather,
namely air temperature, dew point, wind speed, visibility, and barometric
pressure.The results of testing the network with a different number of neurons
in the hidden layer of artificial neural network method with backpropagation
learning algorithms show that the increase in the number of neurons in the
hidden layer is not directly proportional to the value of the accuracy of the weather
forecasts, the increase in the number of neurons in the hidden layer does not
necessarily increase or decrease value accuracy of weather forecasts we obtain
the best accuracy rate of 51.6129% on a network model with three neurons in the
hidden layer.
Penulis: I Made Dwi Udayana
Putra
Kode Jurnal: jpmatematikadd160172
