Article Per Year (5 Year)
p-Index From 2021 - 2026
2.811
P-Index
This Author published in this journals
All Journal Paedagoria : Jurnal Kajian, Penelitian dan Pengembangan Kependidikan EDUKATIF : JURNAL ILMU PENDIDIKAN Jurnal Pendidikan dan Konseling G-Tech : Jurnal Teknologi Terapan Jurnal Riset Pembelajaran Matematika Sekolah Jurnal Statistika dan Aplikasinya Jurnal Pendidikan Jurnal Kependidikan: Jurnal Hasil Penelitian dan Kajian Kepustakaan di Bidang Pendidikan, Pengajaran dan Pembelajaran Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Jurnal Natural
Arman Haqqi Anna Zili
Faculty Of Mathematics And Science Universitas Indonesia
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Immunology & microbiology Languange, Linguistic, Communication & Media Mathematics Neuroscience Physics Social Sciences Other

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Mapping Generational Digital Literacy and Internet Usage Patterns in Open and Distance Learning: A K-Means Clustering Analysis Selly Anastassia Amellia Kharis; Melisa Arisanty; Anton Robiansyah; Arman Haqqi Anna Zili
Jurnal Kependidikan : Jurnal Hasil Penelitian dan Kajian Kepustakaan di Bidang Pendidikan, Pengajaran, dan Pembelajaran Vol. 12 No. 3 (2026): September (IN PRESS)
Publisher : LPPM Universitas Pendidikan Mandalika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jk.v12i3.20354

Abstract

This study aims to map digital literacy and internet-use patterns among multigenerational new students in open and distance learning (ODL) and to determine whether the resulting profiles are differentiated solely by generation or also by occupational and behavioral characteristics. A quantitative exploratory design with K-Means cluster analysis was applied to data from 4,371 new students at Universitas Terbuka Jakarta. The analysis integrated generational profile, occupation, internet-access time, dominant online activity, preferred social-media platform, daily social-media duration, and digital-literacy classification. The Elbow Method indicated a five-cluster solution. The cluster represented 17.00%, 24.94%, 18.39%, 9.40%, and 30.27% of respondents, respectively. Overall, 62.18% of students were classified as High and 35.69% as Very High in digital literacy, while only 2.13% were Satisfactory and none were Low or Very Low. Cluster 3, dominated by Generation Y private employees, contained 97.01% Very High-literacy students, whereas Cluster 5, also dominated by Generation Y private employees, contained 98.49% High-literacy students. Generation Z appeared across three clusters with distinct access timed and online activities. These findings show that generation alone does not adequately explain digital-literacy patterns in ODL; occupational background and digital-use behavior provide additional differentiation. The results supports cluster-based digital-literacy support, flexible learner services, and targeted skill development in ODL.
Co-Authors Agustiani Putri Derick Hendri Dian Lestari Dian Lestari Fauzan Ihza Fajar Hirawati Lubis Martinasari, Made Diyah Putri Melisa Arisanty Melisa Arisanty Nur Mahin Pretty Lawrencia Connery Putri, Agustiani Robiansyah, Anton Selly Anastassia Amellia Kharis Sri Maulidia Permatasari Tri Wijayanti Septiarini