Penerapan Metode Backpropagation Dalam Memprediksi Jumlah Kunjungan Wisatawan Ke Provinsi Nusa Tenggara Barat (NTB) - Komang Triantita Neti Lestari; Moh Ali Albar; Royana Afwani (Informatics Engineering Dept., Faculty of Engineering, University of Mataram, 2019)
Based on the of tourist visits of West Nusa Tenggara from 2013 to 2017 obtained from Tourism Office of NTB Province the number of tourist visits changes every year. a prediction is needed to estimate the number of tourist visits in the upcoming year to help the government in making policy. The Tourism Office currently estimates the tourist visit based on the events that will be carried out. There are no mathematic calculations in estimations. This study uses Backpropagation to predict the number of tourist visits. Backpropagation is a good and accurate in predicting process involving fluctuating data. This study aims to examine the effectiveness of the backpropagation in predicting the number of tourist visits based on the minimum value of the Mean Square Error (MSE). Using a maximum iteration of 1500, learning rate 0.3 and the number of hidden layers 21 produces the minimum MSE value of 0.003901 and the prediction of tourist visits in 2018 has the most tourist arrivals in July 2018 of 465.202 tourists and the lowest visit was in February 2018, which estimated to 236.864 tourists.