Resumen

CHAVEZ-VEGA, N.B.; PEREZ-OLGUIN, I.J.C.; LUVIANO-CRUZ, D.  y  PORTILLO-ESCOBEDO, A.. Application of Data Mining Techniques for Classification: A Case Study in Higher Education. RIIIT. Rev. int. investig. innov. tecnol. [online]. 2024, vol.11, n.66, pp.56-66.  Epub 26-Jun-2026. ISSN 2007-9753.

In Mexico, the EXANI_II assessment instrument has been designed to comprehensively assess academic skills and specific knowledge of applicants to enter higher education. The application of data mining techniques, such as decision trees for classification, can support the detection of vulnerable students. This research compares two decision trees: The J-48 algorithm and the random tree algorithm using the Weka software for its implementation in the EXANI-II database for the evaluation of applicants to enter the Technological University of Chihuahua in 2021. The results are reviewed regarding the accuracy in the classification obtained in each of the algorithms, with the J-48 algorithm having a better performance.

Palabras llave : Educative data mining; J-48 classification algorithm; random tree; Weka software application.

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