Contributions to the Enrollment Process with Data Mining in Private Higher Education Institutions
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| Autores: | , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de Publicación: | 2016 |
| Descripción: | 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. |
| País: | Portal de Revistas UNA |
| Institución: | Universidad Nacional de Costa Rica |
| Repositorio: | Portal de Revistas UNA |
| Lenguaje: | Español Inglés |
| OAI Identifier: | oai:ojs.www.una.ac.cr:article/7452 |
| Acceso en línea: | https://www.revistas.una.ac.cr/index.php/EDUCARE/article/view/7452 |
| Palabra clave: | Educational management educational planning educational administration higher education institutions universities information management Gestión educacional planificación de la educación administración de la educación instituto de enseñanza superior universidad gestión de la información |