PERAMALAN KUNJUNGAN WISATAWAN MANCANEGARA KE PROVINSI BALI MENGGUNAKAN METODE ARTIFICIAL NEURAL NETWORK - WIRANATA, I KETUT RESTU; GANDHIADI, G.K.; HARINI, LUH PUTU IDA (E-Jurnal Matematika; Vol 9 No 4 (2020)DO - 10.24843/MTK.2020.v09.i04.p301, 2020)
Bali has an increasing tourism potential. This is evidenced by the increasing number of foreign tourist visits to Bali Province each year. Although Bali's tourism trends have continued to increase over the past few years, efforts to improve the quality of Bali tourism need to be made. One way is to do forecasting. To support improvement efforts in Bali's tourism sector, the author created a forecasting system for foreign tourists to Bali province using artificial neural network methods with back propagation algorithms. Artificial Neural Networks with back propagation algorithms are neural network algorithms by finding optimal weight values. The forecast results using the binary sigmoid activation function were obtained by 489,862 foreign tourists in November 2019 with MAPE at 1.62% and 487,342 foreign tourists in December 2019 with MAPE of 11.78%. The forecast results using the bipolar sigmoid activation function were obtained by 493,200 foreign tourists in November 2019 with MAPE of 0.95% and 484,090 foreign tourists in December 2019 with MAPE of 12.37%.