Intelligent Data Analysis as a Method of Determining the Influence of Various Factors on the Level of Customer Satisfaction of the Company

This paper analyzes the impact of various factors on the level of satisfaction of passengers using airline services. A dataset of 25 976 airline customers was taken for the work, which contained 22 attributes related to both the services provided by the company and the passengers themselves. Two methods, Kohonen map method and decision tree method were initially used for the analysis. Kohonen maps were used to divide the data into clusters, and cluster parameters were obtained, which showed the significance of the attributes. With the help of decision tree, an attribute significance table was obtained which also showed the level of significance of the attributes. After the first iteration, the decision tree method showed the best result, so this method was chosen for further work. Next, different groups of attributes were analyzed and the errors of the algorithms for each group of attributes were obtained. Correlation analysis was also done which showed the degree of association between the attributes and the target variable. The attributes with greater importance, i.e., having a greater impact on the target variable, were found.