Literature Review: Data Mining For Student Data Classification
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Abstract
The abundance of student data and student graduation number data, hidden information can be found by processing student data to be useful to the university. The processing of student data needs to be done to uncover important information in the form of new knowledge (knowledge discovery) such as information on student data classification based on profile and academic data. Therefore, in this research, the researcher plans to conduct a literature review related to data mining for student data classification with the aim of finding out about data mining data processing classification and collecting all designs used in identifying data starting from problems, methodology, equations and results. For this research, researchers used historical data from students from 2007 to 2011 who had graduated. There were 9 research journals that researchers managed to find, each of which used different algorithms or classification techniques. To conduct a literature review, researchers conducted a journal review using PICOT. The results of this research are the success of researchers in classifying student data using data mining techniques.
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