Designing web-based data mining applications to analyze the association rules tracer study at university using a FOLD-growth method

Tracer study is one of strategy made by university to obtain information and feedback from alumni and stakeholders to measure educational outcomes and improve the process of education and learning in the future. Data mining can be used as a way to collect data feedback from alumni and stakeholders to obtain some useful information. This study has used fast online dynamic-growth (FOLD-growth) to find correlations between different data feedback to determine the pattern of association. The methodology in this study refers to software development methods: analysis system, design system, implementation system and testing system. The result of this study is a design of user interface for web-based data mining applications to analyze the association rules tracer study at university using FOLD-growth method and the design has been tested the acceptance using the method system usability scale (SUS).