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All Journal Jiko (Jurnal Informatika dan komputer) Edukasia: Jurnal Pendidikan dan Pembelajaran
Salsa Dillah
Universitas Negeri Makassar
Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Other

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ANALYSIS OF FUZZY C-MEANS IN PERSONALITY CLUSTERING BASED ON THE OCEAN MODEL Jessicha Pamput; Salsa Dillah; Aindri Muthmainnah; Dewi Fatmarani Surianto
JIKO (Jurnal Informatika dan Komputer) Vol 7 No 3 (2024)
Publisher : Program Studi Teknik Informatika Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i3.8369

Abstract

Personality is the pattern of an individual's behavior in daily life, reflected in their thoughts, feelings, and actions. The Big Five Personality Traits Model, known as OCEAN, helps to understand the complexity of human personality through five main traits. The identification and classification of personality, particularly among students, impacts academic performance, personal development, anxiety levels, and risky behaviors. Collaboration between educators, mental health professionals, and career advisors is crucial to creating an educational environment that supports students' holistic development. The Fuzzy C-Means (FCM) method is used to identify students' personalities with adequate accuracy. This study adopts the OCEAN model with FCM to efficiently identify and classify students' personalities. Data were obtained from 142 respondents, resulting in 27% of respondents being classified in cluster 1, 21% in cluster 2, 18% in cluster 3, 16% in cluster 4, and 18% in cluster 5. This study has important implications for students, educators, and educational institutions to understand that learning patterns, social interactions, and decision-making processes can be influenced by an individual's personality.
Students Understanding of Network Virtualization in Computer Network Courses at Universitas Negeri Makassar Afrisal Arifin; Muh. Alief Rezky Anisar; Fadhlirrahman Baso; Salsa Dillah; Muliadi Muliadi; Dewi Fatmarani Surianto; Jumadi Mabe Parenreng
EDUKASIA Jurnal Pendidikan dan Pembelajaran Vol. 6 No. 2 (2025): Edukasia: Jurnal Pendidikan dan Pembelajaran
Publisher : LP. Ma'arif Janggan Magetan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62775/edukasia.v6i2.1653

Abstract

Students’ understanding of network virtualization concepts in Computer Network courses remains limited, particularly in institutions with restricted access to advanced practical facilities. This study aims to analyze students’ comprehension of network virtualization and its relationship with learning experiences, technical skills, and perceptions of simulation tools. A quantitative cross-sectional survey was conducted with 202 students who had completed the Computer Network course and gained experience using Cisco Packet Tracer. The questionnaire was validated through expert judgment and construct validity testing via Exploratory Factor Analysis, and its reliability was confirmed. Findings indicate that four dimensions conceptual understanding, learning experience, technical skills, and perception of simulation tools consistently form a framework explaining students’ understanding of virtualization. Correlation analysis revealed that technical skills exert the strongest influence, while learning experiences and perceptions contribute additional support to conceptual comprehension. These results highlight the importance of integrating simulation media such as Cisco Packet Tracer into Computer Network courses, not only as a means of developing practical skills but also as a strategy to enhance students’ conceptual grasp of virtualization technologies increasingly demanded in the digital industry. This study contributes to the literature by emphasizing the cognitive dimension of simulation-based learning, an aspect often overlooked in prior research that mainly focused on technical performance.
Co-Authors Afrisal Arifin Aindri Muthmainnah Dewi Fatmarani Surianto Fadhlirrahman Baso Jessicha Pamput Jumadi Mabe Parenreng Muh. Alief Rezky Anisar Muliadi Muliadi