Competency Characteristics of Graduates Viewed from User Satisfaction Using Nonhierarchical Clusters

Muhammad Ikhsan Ghozali, Heri Retnawati

Abstract


This study aims to classify graduates based on the similarity of competency characteristics by referring to the indicators of graduate user satisfaction. The indicators are implementation of Islamic values; integrity, ethics, and morals; expertise based on knowledge (professionalism); foreign language skills; ability to use ICT; communication; teamwork; and self-development. The survey was aimed at graduates of five study programs totaling 211 people. Determination of respondents using the purposive sampling technique. Data was collected through a questionnaire containing statements about the eight indicators. Data analysis uses descriptive and multivariate statistics with the non-hierarchical cluster method or K-Means cluster analysis, assisted with SPSS (Statistical Package for Social Science) software. The results show that based on the similarity of competency characteristics, graduates are grouped into three clusters, namely Cluster 1 with 13.27% with characteristics of graduates with low competence, Cluster 2 with 32.7% with characteristics of graduates with high competence, and Cluster 3 with 54.03% with the characteristics of graduates with moderate competence. Thus, a strategic program that is systematic, comprehensive, and continuous is needed to develop human resources to shape the quality mentality and competence of students and to be competitive with students and by the needs of the workforce or users. For this reason, it is necessary to develop an e-tracer system that is integrated with the campus web and to strengthen synergistic cooperation with stakeholders, including users.

Keywords


Non-hierarchical cluster analysis; K-Means cluster analysis; characteristics of graduate competence.

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