Estudio del rendimiento académico aplicando técnicas de minería de datos.

Educational data mining can be apply to research, prepares and explores the data to get the information that is hidden in them; it is used to help to understand the content of a data repository. During last years, universities have acquired a great interest on the Academic Performance of students and want to determine what factors influence in it, trying to demonstrate which of them are the most affecting academic performance, to do that personal, socioeconomic and institutional data was analyzed from 2010 to 2013 of Loja National University into Energy Area, Industries and Non-Renewable Natural Resources. After that, a study of data mining methodologies, selecting CRISP-DM, it is essential in this study because it contains a guide to develop the project. Also in the application of data mining techniques we chose the Classification that contains RIDOR, ID3, C4.5, PART and JRIP which were used in the RapidMiner tool, it allowed to develop the processes and get results from the model, finally they were analyzed and assessed using real data to determine factors influencing the Academic Performance.

• Egile nagusia: Becerra Encarnación, Darwin Andrés (author)
• Formatua: bachelorThesis
• Hizkuntza: spa
• Argitaratua: 2016
• Gaiak: <RENDIMIENTO ACADÉMICO> <TÉCNICAS DE MINERÍA DE DATOS> <HERRAMIENTAS DE MINERÍA DE DATOS> <RAPIDMINER> <WEKA> <R> <RENDIMIENTO ACADÉMICO><TÉCNICAS DE MINERÍA DE DATOS><HERRAMIENTAS DE MINERÍA DE DATOS>; <RAPIDMINER><WEKA><ORACLE DATE MINING> <METODOLOGÍA PARA MINERÍA DE DATOS>
• Sarrera elektronikoa: http://dspace.unl.edu.ec/jspui/handle/123456789/10988