Open AccessPenerapan Support Vector Regression (Svr) Dalam Memprediksi Jumlah Kunjungan Wisatawan Domestik Ke Bali
Author(s) -
Ni Putu Nanik Hendayanti,
I Ketut Putu Suniantara,
Maulida Nurhidayati
Publication year - 2019
Publication title -
jurnal varian
Language(s) - English
Resource type - Journals
ISSN - 2581-2017
DOI - 10.30812/varian.v3i1.506
Subject(s) - tourism , support vector machine , logistic regression , value (mathematics) , research object , business , geography , computer science , statistics , mathematics , artificial intelligence , business administration , archaeology
Bali is one of the most popular tourism sectors in Indonesia. In the arena of international tourism, the island of Bali is considered as the most famous national destination compared to other destinations. The high level of domestic tourism visits to Bali annually must be strictly noted especially for local governments and Bali provincial tourism agencies in optimizing facilities, infrastructure to the safety of tourists Visit. Therefore, it takes a method that can predict the number of tourists visiting Bali annually. One method used to predict the number of tourists visiting Bali is Support Vector Regression (SVR). SVR is a method to estimate a mapped function from an input object to a real amount based on the training data. SVR has the same properties about maximizing margins and kernel tricks for mapping nonlinear data. Results of this research. Based on forecasting using MAPE value training data obtained by 11.34% while use data testing of MAPE value obtained by 7.30%. Based on the resulting MAPE value can be categorized well for the number of tourism visitors.