AI in Tourism: Leveraging Machine Learning in Predicting Tourist Arrivals in Philippines using Artificial Neural Network

Tourism is one of the most prominent and rapidly expanding sectors that contribute significantly to growth a country’s economy. However, tourism industry has been adversely affected during coronavirus pandemic. Thus, reliable accurate time series prediction tourist arrivals necessary in making decisions strategies develop competitiveness economic industry. In this sense, research aims examine predictive capability artificial neural networks model, popular machine learning technique, using actual statistics Philippines from 2008-2022. The model was trained three distinct data compositions evaluated utilizing different evaluation metrics, identify factors affecting performance determine its accuracy predicting arrivals. findings revealed ANN arrivals, with an R-squared value MAPE 0.926 13.9%, respectively. Furthermore, it determined adding training sets contain unexpected phenomenon, like COVID-19 pandemic, increased model's process. As technique proves accuracy, would be useful tool for government, stakeholders, investors among others, enhance strategic investment decisions.