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All Journal Sistemasi: Jurnal Sistem Informasi Jurnal Proteksi Tanaman Tropika JOEL: Journal of Educational and Language Research eProceedings of Management Multikultural: Jurnal Ilmu Sosial Journal of Embedded Systems, Security and Intelligent Systems jurnal proteksi tanaman tropika Hayak Bamara: Jurnal Pengabdian Masyarakat Jurnal Agroterpadu Ulil Albab Jurnal Ilmiah Bongaya (JIB)
Anshari, Ahmad
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Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Languange, Linguistic, Communication & Media Social Sciences

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Digital Distraction Analysis Using Machine Learning Models to Understand the Impact of Social Media and Risky Use on College Students as Gen Z Mudarris, Mudarris; Anshari, Ahmad; Basirung, Muhammad Romario
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 3 (2025): September 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i4.9830

Abstract

Research on digital distraction among Generation Z students shows that excessive social media use has significant impacts on academic, psychological, and social aspects. Gen Z, who on average own a smartphone before the age of 18 and spend 6–8 hours per day on digital platforms, are susceptible to impaired concentration and decreased academic achievement due to multitasking while studying. Analysis using the Extreme Gradient Boosting (XGBoost) machine learning model identified that the dominant factors influencing digital distraction are negative perceptions of mental health due to social media, feelings of guilt after excessive scrolling, and a tendency to lose time due to short content that offers instant gratification. The study also found that the 18–21 age group with a usage duration of more than six hours per day, especially before bed, is most at risk of experiencing sleep disorders, stress, and a decreased GPA. From a social aspect, the habit of spending time online reduces real interactions and weakens students' social skills. Thus, digital distraction is not only an individual problem, but also a collective one, necessitating interventions in the form of digital literacy education, strengthening study time management, limiting device use before bed, and providing alternative positive activities. This research confirms that the use of machine learning is able to provide an accurate predictive picture of risk patterns, so that the results are useful for academics, technology developers, policy makers, and educational institutions to design more targeted mitigation strategies for the most affected generations.
Co-Authors Adri, Nurul Alhadi, Syarifah Soraya Basirung, Muhammad Romario Chaerunnisa, Chaerunnisa Dewi ANGGRAENI Dewi Dewi Dila, Ratna Dimas Asto Aji An’Amta Eko Nursalim Faelasup, Faelasup Fitrianti Fitrianti, Fitrianti Ismar Hamid Jumiati Jumiati Khairussalam, Khairussalam Laila Laila, Laila Liani, Sava'ah Intan Maylanny Christin Mudarris Mudarris NOOR AIDAWATI Pariati, Ema Safitri, Eva Salamiah . Satriani Satriani