Prediksi Tingkat Kedatangan Wisatawan Asing Menggunakan Metode Backpropagation

Salman Alfarisi Salimu (Universitas Putra Indonesia YPTK Padang)
Yuhandri Yunus (Universitas Putra Indonesia YPTK Padang)

Jurnal Informatika Ekonomi Bisnis
Vol. 2, No. 4 (December 2020)

The tourism industry is always growing and plays an important role in the national economy, both as the second largest contributor to foreign exchange and as a large labor absorber. This study aims to optimize production using the Artificial Neural Network (ANN) method. The technique used is Backpropagation. The data processed is data on the number of foreign tourists from 2017 to 2019 in the Mentawai Islands. The results of the momentum obtained are 2-5-1 on the division of data into 2, namely training data for 2017 and 2018 and test data for 2019. The optimal prediction result is 0.99847, so this research is very helpful in predicting the arrival rate of foreign tourists in Mentawai Islands.