Análisis inteligente de datos para identificar los factores que influyen en la deserción de los estudiantes de la unidad de admisión y nivelación de la Universidad Técnica Estatal De Quevedo

The present research focuses on the search of knowledge of the information repositories of the students of the leveling course of the Admission and Registration Unit of Quevedo State Technical University. This information was characterized by being varied and stored some maps of the reality of students. The present project shows the methodology to obtain the factors that influence student dropout. This information will be taken from a data set present in the Admission and Registration Unit of Quevedo State Technical University. In order to obtain the desertion factors it was necessary the application of data mining and an intelligent analysis process. The present research applies the processes of knowledge extraction through the use of decision trees, which provided a series of models that could be compared to determine the most optimal and the results to be used, allowing to detect the variables or factors most influential in The student desertion of the leveling course of the Admission and Registration Unit of Quevedo State Technical University. Finally, the conclusions and recommendations are established, which mainly establish the importance of applying this type of research at the educational level and the possibility of expanding the present research with the use of other algorithms for data modeling.