Forecasting Tourist Visit Using the Vector Autoregressive Exogenous Method (VARX) - Erni Muschilati; Nursyiva Irsalinda (Universitas Ahmad Dahlan, 2020)
Forecasting is an activity to predict what will happen in the future by paying attention to information from the past and the present. A regression model that explains the past movement of the variable itself and also all other variables without distinguishing which endogenous and exogenous variables are called Vector Autoregressive (VAR). But in practice, endogenous variables are supported by exogenous variables. The Vector Autoregressive Exogenous (VARX) model is a development of the VAR with the addition of exogenous variables. The purpose of this study is to form the best model in the VAR method with the addition of an exogenous variable in the form of an effect calendar for forecasting the number of tourists coming to the Special Region of Yogyakarta (DIY). The data used in this study are time series data for 10 years from January 2009 to December 2018 in the form of tourist visit data in the Special Region of Yogyakarta (DIY). The results obtained indicate that the effect calendar variable that affects tourist visitor data in DIY is at Christmas. After being analyzed using MAPE, the best model is the VARX (1.0) model which produces a smaller. So, it can be concluded that the VARX model with the addition of an effects calendar is suitable for predicting tourist visits