Backpropagation algorithm modeling to predict the number of foreign tourist visits to indonesia via air gates - Astuti, Febriani; Bekti, Rokhana Dwi; Br Keliat, Aurora Arianita; Sebo, Theodorina Inya (Universitas Islam Negeri Raden Intan Lampung, 2023)
The tourism sector is a supporting sector for the Indonesian economy. One of the important actors in Indonesian tourism is foreign tourists. After the COVID-19 pandemic, the trend of foreign tourist visits to Indonesia has increased. The Central Statistics Agency (BPS) recorded that foreign tourist visits to Indonesia during 2022 reached 5.47 million. This figure has increased by 251.28% compared to the 2021 period. According to BPS, one of the gates most accessed by foreign tourists is the air gate. Based on these conditions, this research aims to predict the number of foreign tourists coming to Indonesia via air gates. The method used to predict is the backpropagation algorithm. The use of the backpropagation algorithm is able to provide prediction results with the highest level of accuracy of 91.40% for tourist visits at Ngurah Rai Airport, Bali. Furthermore, an MSE value of 0.056 was obtained. Thus, predictions using the backpropagation algorithm can be said to be good and quite accurate and can be used for prediction calculations in the following year.