Flight ticketing analysis with data mining methods

Data mining used in many sectors also has great potential in terms of airline companies. Data mining methods are used effectively in strategic decisions that directly touch the critical customer. The process of processing the data into information is called data mining. Association rules and Apriori algorithm are frequently used methods in the field of data mining. In this thesis, firstly data mining was explained and after the introduction of the methods to be used in the study, the ticketing data of the passengers of the 2016 summer and winter periods of Turkish Airlines were discussed. After pre-processing and cleaning processes, 824 rules were applied to the flight ticketing data consisting of 2036113 lines by using Association Rules and Apriori Algorithm. By interpreting the obtained rules and evaluating the effects of the rules, suggestions are presented that can contribute positively to the customer experience. Keywords: Data Mining, Apriori Algorithm, Association Rules, Flight Ticketing