Özet:

Access to useful information from data and the process of examining information is data mining. Artificial nerve networks are one of the methods used in data mining studies. Programs are created by simulating the neurons formally and functionally with artificial nerve networks. Artificial nerve networks based on mathematical methods can be used for prediction purposes. In a predictive problem based on the cause and result relationship, the input of the artificial nerve network varies independently, and its output is dependent. It can be considered a non-real regression model. In this study, a predictive problem in the tourism industry has been modeled and analyzed with the data mining tool WEKA using artificial nerve network to solve. The data of the monthly tourism revenues between 1969 and 2017 published by the Turkish Statistical Bureau have been used. By modeling these data with artificial nerve networks, 2018 data was predicted. Because the real data is used, the amount of errors obtained from the model can be estimated for the monthly tourism income that can be obtained in 2019. It is important to be able to adapt to the change in the tourism sector and make appropriate predictions in order to manage the competition. Forecasts for the tourism development plans that will be prepared by the central and local public authorities can be grounded. Tourism in Turkey can be achieved. This predictive work will guide tourism managers and local governments in future decision-making and planning.