Correlation Analysis of Student Activity Units on  Soft Skill Development using the Apriori Algorithm

Putri Amanda Rossya; A M H Pardede; I Gusti Prahmana

doi:10.59934/jaiea.v5i1.1506

Authors

Putri Amanda Rossya STMIK Kaputama
A M H Pardede STMIK KAPUTAMA
I Gusti Prahmana STMIK KAPUTAMA

DOI:

https://doi.org/10.59934/jaiea.v5i1.1506

Keywords:

Apriori Algorithm, Association Rules, Data Mining, Soft Skills, Student Activity Units

Abstract

This study aims to analyze the correlation between Student Activity Units (UKM) and the improvement of students’ soft skills using the Apriori algorithm. Student Activity Units serve as a platform for self-development that can enhance non-technical skills such as communication, teamwork, problem solving, responsibility, and creativity. The research data were obtained from students participating in various activity units, including arts, religion, technology, sports, entrepreneurship, environment, and social organizations. By applying the Apriori algorithm through RapidMiner software, several association rules with high support and confidence values were discovered, indicating significant relationships between participation in specific activity units and the enhancement of certain soft skills. The results demonstrate that involvement in technology and innovation, arts, and social activity units contributes significantly to improving students’ communication, teamwork, and creativity. These findings are expected to serve as a reference for higher education institutions in designing more strategic student activity programs to support soft skill development.

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