Analysis Prediction of Prambanan Temple Visitors with Fuzzy Time Series Chen Model and Seasonal Auto Regressive Integrated Moving Average (SARIMA) Model

Abstract

The number of visitors in tourist attractions are almost always changes each time, even for tourist attractions that are already well-known among local and foreign people, usually will tend to increase at certain times, as in the Prambanan Temple. Based on data from TWC (Taman Wisata Candi) unit office, the number of visitors of Prambanan Temple during holidays at the end of 2018 increased by 8% from the previous year. Because of its increase, the manager of tourist attractions must always try to provide the best service. Therefore, the manager of Prambanan Temple needs to know the prediction of the number of visitors in the future so that they can prepare services and innovations to increase its attractiveness. The data of Prambanan Temple visitors number is seasonal, so the visitors number prediction at Prambanan Temple will be determined using the method for seasonal data. This research tries to compare the two methods, namely Fuzzy Time Series Chen Model and Seasonal Auto Regressive Integrated Moving Average (SARIMA) Model. The results of these methods are the visitors number prediction with different errors, so it can be seen which method is better between the two.