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A Better Prediction for Higher Education Performance using the Decision Tree

  • Hilal, Anwar (Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University) ;
  • Zamani, Abu Sarwar (Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University) ;
  • Ahmad, Sultan (Department of Computer Science, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University) ;
  • Rizwanullah, Mohammad (Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University)
  • Received : 2021.04.05
  • Published : 2021.04.30

Abstract

Data mining is the application of specific algorithms for extracting patterns from data and KDD is the automated or convenient extraction of patterns representing knowledge implicitly stored or captured in large databases, data warehouses, the Web, other massive information repositories or data streams. Data mining can be used for decision making in educational system. But educational institution does not use any knowledge discovery process approach on these data; this knowledge can be used to increase the quality of education. The problem was happening in the educational management system, but to make education system more flexible and discover knowledge from it huge data, we will use data mining techniques to solve problem.

Keywords

References

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