Comparison of support vector machine and backpropagation models in forecasting the number of foreign tourists in Bali province

Jurnal Teknologi dan Sistem Komputer

Imelda Alvionita Tarigan¹  I Putu Agung Bayupati¹  Gusti Agung Ayu Putri¹ 

[1] Department of Information Technology,Universitas Udayana, Bukit Jimbaran, Badung, Bali, Indonesia 80361, Indonesia;

关键词: pariwisata;    svm;    kernel;    backpropagation;   

DOI  :  10.14710/jtsiskom.2021.13847

来源: DOAJ

【 摘 要 】

Tourism in Bali is one of the major industries which play an important role in developing the global economy in Indonesia. Good forecasting of tourist arrival, especially from foreign countries, is needed to predict the number of tourists based on past information to minimize the prediction error rate. This study compares the performance of SVM and Backpropagation to find the model with the best prediction algorithm using data from foreign tourists in Bali Province. The results of this study recommend the best forecasting using the SVM model with the radial kernel function. The best accuracy of the SVM model obtained the lowest error values of MSE 0.0009, MAE 0.0186, and MAPE 0.0276, compared to Backpropagation which obtained MSE 0.0170, MAE 0.1066, and MAPE 0.1539.

【 授权许可】

Unknown