The Forecasting Technique Using SSA-SVM Applied to Foreign Tourist Arrivals to Bali

Yosep Oktavianus Sitohang, Yudhie Andriyana, Anna Chadidjah


In order to achieve a targeted number of foreign tourist arrivals set by the Indonesian government in 2017, we need to predict the number of foreign tourist arrivals. As a major tourist destination in Indonesia, Bali plays an important role in determining the target. According to the characteristic of the tourist arrivals data, one shows that we need a more flexible forecasting technique. In this case we propose to use a Support Vector Machine (SVM) technique. Furthermore, the effects of noise components have to be filtered. Singular Spectrum Analysis (SSA) plays an important role in filtering such noise. Therefore, the combination of these two methods (SSA-SVM) will be used to predict the number of foreign tourist arrivals to Bali in 2017. The performance of SSA-SVM is evaluated via simulation studies and applied to tourist arrivals data in Bali. As the results, SSA-SVM shows better performances compare to other methods.


foreign tourist, singular spectrum analysis, support vector machine

Full Text:



Article Metrics

Abstract view : 427 times
PDF - 141 times


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

TELKOMNIKA Telecommunication, Computing, Electronics and Control
ISSN: 1693-6930, e-ISSN: 2302-9293
Universitas Ahmad Dahlan, 4th Campus, 9th Floor, LPPI Room
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191
Phone: +62 (274) 563515, 511830, 379418, 371120 ext. 4902, Fax: +62 274 564604