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All Journal Sistemasi: Jurnal Sistem Informasi Journal of Embedded Systems, Security and Intelligent Systems
Ahmad Anshari
Politeknik Nusantara Makassar
Computer Science & IT Electrical & Electronics Engineering

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A Model Design of Lesson Learned System (LLS) for Accountability Report: A Case Study of Tourism Promotion Agency Anshari, Ahmad
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.3655

Abstract

The tourism industry is one of valuable industries in Indonesia that needs a high level of expertise through the knowledge management systems in order to improve the tourism service delivery quality performance. Problems faced by this institution is the complexity and hardness in defining and enhancing knowledge through an accountability report, this is due to the lack of management through the process of applying an accountability report. This attracts us to make a research about the users’ perception towards the lesson learn system prototype where this study will examine the users’ perception in designing Lesson Learn System based on the requirements in order to enhance employees knowledge through an accountability report.. After examining the perception of the lesson learn system users, we will design Lesson Learn System prototype by using User Centered Design that describe the relationship between the lesson learn system and its users by specifying the context of using the lesson learn system in tourism. This also will specify the requirements needed for the lesson learn system that help for designing the Lesson learn system design solution.
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; Ahmad Anshari; Muhammad Romario Basirung
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 Mudarris Mudarris Muhammad Romario Basirung