Exploring Digital Transformation Readiness: Unveiling Hidden Patterns Through K-Means Clustering - Lalita Vistari; Issy Yuliasri; Yuliati -; Adrallisman -; Melfa Lamria Berliana Lumbantoruan (Mimbar Ilmu, 2025)
The rapid digital transformation in higher education requires students to have advanced digital skills, ethical awareness, and effective communication. However, many studies overlook the diversity within student populations, particularly in terms of digital readiness. This research addresses this gap by examining students' digital construction variations through the use of K-Means clustering. The study adopts a mixed-methods approach, combining a survey on technology usage, attitudes, and communication with qualitative interviews. The analysis identifies two distinct student clusters: "Basic Learners," who demonstrate lower digital readiness, and "Digital Pioneers," who exhibit advanced digital skills. The validity of these clusters is confirmed through the Silhouette Score and ANOVA (p < 0.05), which reveal significant differences in digital readiness. The findings suggest that students with lower academic achievement perform better with moderately challenging digital tasks when provided with additional resources. In contrast, older students face more complex digital challenges. This highlights the need for higher education institutions to develop more inclusive, tailored strategies that address the diverse digital needs of students.