Estimation of dental tourists' satisfaction via data mining

Objective: The research was done to be able to estimate dental tourists' service satisfaction states by using the data mining. Material and Methods: As based on quantitative analysis and data mining processes, the research was done in 2023, with 314 dental tourists, who received services at a private dental tourism clinic in the Kuşadası district of Aydın province. The data was initially collected through a survey, and these data were evaluated via statistical techniques such as Pearson Coefficient, Kolmogorov Smirnov Test, Mann-Whitney U Test and Kruskal-Wallis Test. Following to that, various factors were identified by using the factor analysis. For the data mining process, the decision trees algorithm was used accordingly. Results: It was understood that there was no significant relationship between the participating dental tourists' age and satisfaction level (p=0.066>0.05) while there was a significant difference in their satisfaction state according to the gender (p=0.000<0.05). It was also seen that the dental tourists' satisfaction levels have significant differences according to the citizenship (p=0.000<0.05), education level (p=0.003<0.05) and income status (p=0.000<0.05). Also these differences were specific in terms of demographic classes. Based on the survey feedback, 4 factors corresponding to satisfaction levels were determined. With the data mining decision trees algorithm, which was applied on the dataset covering demographic data and feedback on 4 factors, a 96% accuracy rate was achieved for the training phase while it was 80% for the testing phase. Conclusion: It was concluded that different demographic data and factors are effective in dental tourists' service satisfaction, and the satisfaction state for potential dental tourists can be effectively predicted with a data mining system, which is created based on these parameters. Keywords: Health Tourism, Dental Tourism, Data Mining, Service Satisfaction.