AbstractsComputer Science

The scope of this project is to explore the possibilities in applying data mining techniques for discovering new knowledge about student absenteeism in primary school. The research consists in analyzing a large dataset collected through the digital protocol system E-protokol. The data mining techniques used for the analysis involves clustering, classification and association rule mining, which are utilized using the machine learning toolset WEKA. The findings includes a number of suggestions for where and with what purpose the tested data mining techniques can be applied, as well as a discussion of the implications this could have. In the end of the report, we address a number of shortcomings in the project along with suggestions for future research.