PERAMALAN KUNJUNGAN WISATAWAN MANCANEGARA KE INDONESIA MENGGUNAKAN METODE SUPPORT VECTOR REGRESSION DAN BACKPROPAGATION - Purwati (2020)
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%.