Prediction of Foreign Tourist Arrivals in Bali Using Support Vector Machine Algorithm and Linear Regression

Arif Lukman Hakim, Indra Wibisono, Yuanita Octoria, Andi Nugroho


Bali Island, a famous tourist destination in Indonesia, has experienced ups and downs in its tourism sector. To anticipate the arrival of international tourists, a thorough analysis and prediction approach is necessary. The main objective of this research is to analyse and predict foreign tourist arrivals in the coming year. The use of machine learning algorithms can be important in analysing data and forecasting the development of international tourist arrivals. This research details the use of several machine learning algorithms, namely Support Vector Machine (SVM), and Linear Regression. The test results show that the SVM programme evaluation provides accurate predictions with a low error rate on the test data. Whereas, the error rate of the Linear Regression programme evaluation is slightly higher. However, the model is still able to make good predictions on the test data.

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