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Revista Electrónica Educare
versión On-line ISSN 1409-4258versión impresa ISSN 1409-4258
Resumen
ESTRADA-DANELL, Rafael Isaac; ZAMARRIPA-FRANCO, Roman Alberto; ZUNIGA-GARAY, Pilar Giselle y MARTINEZ-TREJO, Isaías. Contributions to the Enrollment Process with Data Mining in Private Higher Education Institutions. Educare [online]. 2016, vol.20, n.3, pp.217-237. ISSN 1409-4258. http://dx.doi.org/10.15359/ree.20-3.11.
This article aims to analyze how data mining (DM) optimizes the enrollment process, with the intention of designing a predictive model to manage private enrollment for higher education institutions of Mexico. It analyzes the current status of the higher education institutions in relation to its enrollment process and the application of the DM. With a correlational method, a dataset (DS) was used to model an entropy decision tree with the help of Rapid Miner software. The results show that it is possible to build and test a predictive model management of private enrollment for higher education institutions of Mexico as the ZAM&EST model proposed by the authors.
Palabras clave : Educational management; educational planning; educational administration; higher education institutions; universities; information management.