<![CDATA[Migration plays an important role that needs to be considered in the national development strategy. The rapid rate of migration require attention such as demand for urban infrastructure, housing, and public services. Google Trend is one of the Big Data sources that can be used to see the possibility of migration through certain keyword searches. This study focuses on using of Google Trend data as additional data to improve forecasting accuracy. The forecasting is carried out using two time series methods, Seasonal Autoregressive Integrated Moving Average (SARIMA) and Vector Autoregression (VAR) with or without Google Trend variables to see model performance. As a result, using Google Trend data helps improve model performance to predict the possibility of migration in the short and long term, as indicated by a decrease in statistical measures such as RMSE, MSE, and MAE when the model is used to predict short and long-term inbound migration.]]>
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