Prediction of Tourist Arrivals to the Island of Bali with Holt Method of Winter and Seasonal Autoregressive Integrated Moving Average (SARIMA)

Abstract

The tourism sector is one of the contributors of foreign exchange is quite influential in improving the economy of Indonesia. The development of this sector will have a positive impact, including employment opportunities and opportunities for entrepreneurship in various industries such as adventure tourism, craft or hospitality. The beauty and natural resources owned by Indonesia become a tourist attraction for domestic and foreign tourists. One of the many tourist destination is the island of Bali. The island of Bali is not only famous for its natural, cultural diversity and arts but there are also add the value of tourism. In 2015 the increase in the number of tourist arrivals amounted to 6.24% from the previous year. In improving the quality of services, facing a surge of visitors, or prepare a strategy in attracting tourists need a prediction of arrival so that planning can be more efficient and effective. This research used  Holt Winter's method and Seasonal Autoregressive Integrated Moving Average (SARIMA) method  to predict tourist arrivals. Based on data of foreign tourist arrivals who visited the Bali island in January 2007 until June 2016, the result of Holt Winter's method with parameter values α=0.1 ,β=0.1 ,γ=0.3 has an error MAPE is 6,171873. While the result of SARIMA method with (0,1,1)〖(1,0,0)〗¹² model has an error MAPE is 5,788615 and it can be concluded that SARIMA method is better.

Keywords: Foreign Tourist, Prediction, Bali Island, Holt-Winter's, SARIMA.