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Journal : Jurnal MediaTIK

Risiko Cyberbullying di Instagram: Studi Persepsi Mahasiswa Terhadap Risiko, Pengalaman, dan Regulasi Pencegahannya: Risk of Cyberbullying on Instagram: A Study of Students' Perceptions of Risks, Experiences, and Preventive Regulations Rezky, Muhammad; Ilmi, Nurul; Nurjannah, Elma; Andi Dio Nurul Awalia; Haris
Jurnal MediaTIK Volume 8 Issue 2, Mei (2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Cyberbullying di Instagram telah menjadi masalah yang semakin mengkhawatirkan dalam beberapa tahun terakhir. Penelitian ini bertujuan untuk mengidentifikasi faktor-faktor penyebab cyberbullying di platform tersebut serta dampaknya terhadap kondisi psikologis pengguna, khususnya di kalangan mahasiswa. Penelitian ini menggunakan pendekatan kuantitatif dengan desain cross-sectional. Data dikumpulkan melalui kuesioner yang diisi oleh 100 mahasiswa dari jurusan Teknik Informatika dan Komputer yang memiliki pengalaman terkait cyberbullying. Instrumen penelitian menggunakan skala Likert untuk mengukur persepsi responden mengenai berbagai bentuk dan dampak cyberbullying. Hasil penelitian menunjukkan bahwa penggunaan media sosial yang berlebihan, norma sosial di kalangan pengguna, dan kecanduan terhadap media sosial berkontribusi terhadap munculnya perilaku cyberbullying. Selain itu, sebagian besar responden melaporkan dampak psikologis negatif akibat pengalaman tersebut. Penelitian ini menyarankan pentingnya regulasi yang lebih ketat dari platform media sosial dan edukasi etika komunikasi untuk mengurangi dampak negatif cyberbullying. Penelitian ini berkontribusi dalam memahami keterkaitan antara norma sosial, penggunaan media sosial, dan etika komunikasi dalam upaya pencegahan cyberbullying di Instagram, serta merekomendasikan pendekatan edukatif untuk meningkatkan kesadaran akan dampak psikologis cyberbullying, khususnya di kalangan mahasiswa Teknik Informatika.
The Role of Artificial Intelligence in Improving Students' Self-Regulated Learning through Adaptive Feedback in Facing Socioeconomic Inequality Nurjannah, Elma; Andi Dio Nurul Awalia; Agusnaya, Nurrahmah; Fakhri, M. Miftach
Jurnal MediaTIK Volume 8 Issue 3, September (2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/mediatik.v8i3.10808

Abstract

The transformation of higher education through artificial intelligence is increasingly relevant in addressing the challenges of access, quality, and diversity of student learning needs. Although this technology promises a more adaptive and personalized learning experience, its use is still influenced by socioeconomic inequalities that create gaps in access to and perceptions of technology. This study aims to analyze how artificial intelligence, through cognitive and affective feedback, can improve students' independent learning abilities, with motivation as an intermediary variable and socioeconomic status as an external factor that influences the effectiveness of technology utilization. This study uses a quantitative approach with a cross-sectional design. The instrument, in the form of a structured questionnaire with a Likert scale, was distributed to 450 students from various universities in Indonesia. The questionnaire was compiled based on theoretical indicators from five main constructs and validated through convergent validity and construct reliability tests using outer loading and average variance extracted. The data were analyzed using partial least squares structural equation modeling to test direct and indirect causal relationships, as well as the mediating role between variables. The main results show that artificial intelligence supports students in understanding material in a structured manner and increases emotional engagement, which ultimately strengthens self-regulation and meaning-making in the learning process. Motivation was found to be a significant link between technology and learning outcomes, while socioeconomic background significantly influenced the intensity of technology use. This study concludes that artificial intelligence can be an effective and inclusive learning innovation if it is developed with consideration of cognitive, affective, motivational, and social inequality aspects in education.