Application of K-Means Cluster Analysis for Grouping State Islamic University in Indonesia based on the Readiness Indicators for World Class University (WCU)

Marhayati Marhayati, Arini Mayan Fa'ani, Sulistya Umie Ruhmanasari, Siti Faridah

Abstract


Based on Moscow Ranking 2021, State Islamic University in Indonesia is still lower than other non-Islamic State University. This shows that the mapping of higher education readiness is an important aspect in preparation for WCU. Thus, there is a need for more in-depth research related to the level of readiness of universities. This study aims to determine the data description of the readiness of State Islamic Religious Colleges (PTKIN) to World Class University (WCU) and classify them based on that readiness. Quantitative methods are used in this study. The data were analyzed by K-Means Clustering. The data used in this research obtained from the Ministry of Religion's e-SMS Diktis system. The e-SMS system is a collection of data in each unit at a university based on WCU indicators, namely Good Governance University (GUG), University's Performance Improvement (UPI), Competitive Advantages University (CAU), and Global Recognition University (GRU). The results of the analysis show that from the four indicators it has not been able to achieve 100%. In addition, there are three clusters produced, namely PTKIN is very ready, ready, and not ready to go to World Class University (WCU). PTKIN need hard work in each indicator to be an international standard

Keywords


Clustering, K-Means, World Class University, e-SMS

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References


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DOI: https://doi.org/10.18860/ca.v8i2.18046

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