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All Journal Jurnal Teknodik Jurnal Pengabdian Journal of Embedded Systems, Security and Intelligent Systems
Basirung, Muhammad Romario
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Pengembangan Media Sistem Kerja Sensor Berbasis Internet of Things (IoT) pada Program Industri 4.0 SMK Basirung, Muhammad Romario; Wahyudi
Jurnal TEKNODIK Jurnal Teknodik Vol. 27 No. 2, Desember 2023
Publisher : Pusat Data dan Teknologi Informasi Kementerian Pendidikan Kebudayaan, Riset dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32550/teknodik.vi.1084

Abstract

The development of the industrial revolution 4.0 era and the technology has been influencing various sectors, including education in Vocational High Schools. This educational institution needs to improve students' knowledge and skills in the industry so that they have high competitiveness in the era of the industrial revolution 4.0. One of the most important fields of science in the industrial revolution 4.0 is the Internet of Things (IoT). Therefore, this research aims to develop an IoT-based microcontroller trainer media as an essential learning material in SMK that is valid, practical, and effective. The research method used is Research and Development (R&D) with the modification of 2 development models, namely Waterfall and Prototype. The modification results in syntax/development stages suitable for designing and developing learning products, namely IoT-based sensor learning media. This research is conducted in 5 stages, namely 1) Needs Analysis; 2) Design; 3) Feasibility Test; 4) Implementation; and 5) Evaluation and Revision. The result shows that the IoT-based microcontroller trainer media developed has a very high validity in terms of media and material presented. In addition, the implementation of this trainer media also receives positive responses from students who state that the use of this media trainer is very good.
Implementasi Reaktor Biogas Berbasis Komunitas untuk Kemandirian Energi dan Keberlanjutan Lingkungan di Desa Pesisir Sulawesi Selatan Amiruddin, Amiruddin; Baharuddin, Fiskia Rera; Mudarris, Mudarris; Hidayat, Akmal; Basirung, Muhammad Romario
Jurnal Pengabdian Vol. 4 No. 2 (2025): Juli-Desember
Publisher : Bengkulu Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58222/jp.v4i2.1718

Abstract

This community service program aims to implement a community-based biogas reactor as an alternative energy solution and sustainable livestock waste management system in Laikang Village, Mangarabombang District, Takalar Regency, South Sulawesi, Indonesia. The main problems faced by the partner community were the accumulation of cattle manure causing environmental pollution and the high dependence on subsidized liquefied petroleum gas (LPG). The program was carried out for eight months using a participatory and appropriate technology approach, involving the community at every stage, including planning, reactor construction, technical training, and performance evaluation. A 6 m³ anaerobic biogas reactor was successfully designed, built, and operated using cattle manure and water in a 1:1 ratio. Field measurements showed that the reactor produced 1.0–1.2 m³ of methane gas per day, replacing approximately 30–35% of household LPG consumption. The fermentation process also produced 10–15 liters of slurry per day, which was further utilized as liquid organic fertilizer. The program’s impact includes a 70% reduction in open livestock waste, 30% reduction in household energy costs, and the establishment of a Village Energy Self-Reliance Group (Kelompok Energi Mandiri Desa – KEMD) responsible for long-term management of the biogas system. The results demonstrate that community-based biogas technology effectively promotes rural energy independence, environmental awareness, and local economic empowerment. This initiative aligns with the Sustainable Development Goals (SDGs), particularly Goal 7 (Affordable and Clean Energy) and Goal 13 (Climate Action). The implemented model can serve as a replicable prototype for other coastal and rural communities in Indonesia with similar livestock and energy challenges.
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 Akmal Hidayat Amiruddin Amiruddin Anshari, Ahmad Fiskia Rera Baharuddin Mudarris Mudarris Mudarris, Mudarris WAHYUDI