Analysis of university preferences for high school students studying in informatics with artificial intelligence methods

Nowadays, with the increase in data producing and storing resources, there has been a rapid increase in the population of large and complex data. Simultaneously, computers and software with the ability to calculate have emerged with the ability to calculate. However, extracting meaningful information from complex data is still among the challenges that must be overcome. Data mining science is looking for new ways and methods in cooperation with many disciplines to overcome these challenges. In particular, artificial intelligence algorithms play an active role in revealing complex relationships in data. Today, there are many complex problems and one of them is to redirect part of the high school students can provide the highest yield in the university or reveal the factors affecting this choice. In this thesis, it is aimed to reveal the factors affecting the selection of high school students in the department of information technology with the association rules. The data used in the study were obtained by open data collection method with a questionnaire that the participants answered voluntarily. These data were used for association rule inferences. The main purpose of the analysis process is to reveal whether the students who determined their departments during their high school years continue in the same department or field at the university and the reasons for this choice. It has been ensured that the rules of association of the courses that students like to study, their areas of interest and the activities they engage in are determined. Thus, it will be possible to direct the students whose areas of interest are determined to the right departments and preferences. The findings showed that there are some features that affect the students' choice of department they want to study.