Abstract :
Tourism is one of the important sectors in the growth of Indonesia’s economy. To
be able to achieve the target and increase foreign tourist visits to Indonesia it is
necessary to plan appropriate promotion and sustainable development that must be
in line with the development of foreign touriststo be in target, effective and efficient.
In this study forecasting to the level of foreign tourists visiting Indonesia in order
to obtain accurate data. Forecasting is done by comparing 3 forecast methods, viz.
traditional method, Support Vector Regression (SVR), and Backpropagation
Neural Network (BPNN) method. In this research, there are 36 monthly visit data
from 2017 to 2020 that are used to forecast. The result of this research indicates
that the best forecasting is done by the Support Vector Regression (SVR) method
with a MAPE value is 2.5614 % whereas, Backpropagation Neural Network
(BPNN) has a MAPE value 31.3777%.