ABSTRACT
Introduction:
Finding the factors that contribute to success in student performance or failure is necessary for every teacher. Data mining, which is already used in companies for management processes, can be essential in this research.
Objective:
Discuss the data mining algorithms application in sports performance management.
Method:
A database was developed considering seasonal factors, health benefit index, and sports behavior characteristics. The data were entered under fuzzy logic, processed, and analyzed in IBM SPSS Modeler Software. Decision-making efficiency was improved with the target base interpolation analysis and the C spatial noise reduction methods. The fidelity of sports behavior was consolidated under Gauss time series analysis.
Results:
The relationship between the mining algorithm to find the existing problems and the association results in the mining rules provided valuable information for improving health guidelines to the physical activity students.
Conclusion:
The original data from the educational system can be transformed into useful information through the association rules algorithm, and the relationship between the performance can be obtained, providing the improvement in the decision making for the benefit of the physical level of the students. Evidence Level II; Therapeutic Studies – Investigating the results.
Keywords:
Athletic Performance; Association Rules; Data Mining
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