Time Series Analysis on Tourists’ Arrival to Maldives After COVID-19 Pandemic

Abstract

Coronavirus disease 2019, also known as COVID-19, is a highly contagious respiratory infection caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This pandemic has significantly impacted various industries, and tourism is the one of the most affected. In Maldives, tourist arrivals play a pivotal role in the country's tourism industry. The primary aim of this research is to analyze and compare the trends and patterns in tourist arrivals to the Maldives before, during, and after the COVID-19 pandemic, by employing the graphical analysis techniques. The dataset used is based on the monthly data of tourists' arrival to Maldives, from January 2000 to February 2023. The number of tourist’s arrival from five countries which are Malaysia, Singapore, Thailand, Indonesia, and Philippines to Maldives are analysed using the Box-Jenkins method and the Singular Spectrum Analysis (SSA). Both methods are then compared to get the best model and used for forecasting. Using the accuracy measurements as the Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE), the results show that the best model for Malaysia, Indonesia and Phillipines is Box Jenkins model. Meanwhile, the best model for Singapore and Thailand is SSA model. Box Jenkins model provide better forecasting, but SSA show conversely. Further studies should explore the combination of Box-Jenkins models and Singular Spectrum Analysis. Prediction accuracy is assessed using this approach.