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PELATIHAN ARTIFICIAL INTELLIGENCE UNTUK PENINGKATAN LITERASI DIGITAL REMAJA PEDESAAN: STUDI PENGABDIAN BERBASIS INTERVENSI Erlan Darmawan; Nani Ronsani Thamrin; Dewi Sukma Nurhana; Tiara Astuti; Rohmalia; Aditiya; Muhammad Pakhriz Alif
Jurnal Abdi Inovatif : Pengabdian kepada Masyarakat Vol. 5 No. 1 (2026): Jurnal Abdi Inovatif : Pengabdian kepada Masyarakat
Publisher : Universitas Nusa Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31938/jai.v5i1.956

Abstract

This community service program was implemented to address low digital literacy among rural youth and to provide limited access to Artificial Intelligence (AI) training. Although smartphone usage among teenagers is quite high, it remains largely focused on entertainment and social media, so the productive use of digital technology has not developed to its full potential. To address this, the activity was carried out with youth from Pajawan Kidul Village, Lebakwangi District, Kuningan Regency, aiming to improve their basic understanding of AI and digital literacy skills in rural areas. The implementation method used a participatory approach through socialization, AI practice, mentoring, project-based learning, and evaluation using pre- and posttests. During this process, participants received training on using various AI-based applications, including ChatGPT, QuillBot, Canva AI, and Tome AI. In total, 30 village youth were involved in all program activities. As a result, the activity showed an increase in participants' understanding of AI concepts and their application in daily activities. The average score of participants increased from 57.44 before the training to 82.66 after the activity ended, an increase of approximately 43.9%. Notably, there was significant growth in participants' understanding of how AI can support more productive activities. Beyond improving participants' skills, this activity led to five AI-based mini-projects and the formation of the "Youth Tech Club Pajawan Kidul" learning community to sustain digital learning in the village. In summary, AI training that emphasizes hands-on practice and a contextual approach can be an effective way to strengthen digital literacy while reducing the technology gap among rural youth.
Computer-based animation system for reading literacy in students with intellectual disabilities Erlan Darmawan; Nani Ronsani Thamrin; Aji Permana; Aah Sumiah
Bulletin of Electrical Engineering and Informatics Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i4.11212

Abstract

Reading literacy is a central challenge for students with intellectual disabilities, affecting skills such as letter recognition, vocabulary comprehension, and meaning retention. In Indonesian special schools, the problem is exacerbated by limited adaptive computer-based learning media and the lack of quantitatively evaluated digital interventions. To address this, the study designs and evaluates a computer-based digital animation video learning system developed using accessibility-focused human–computer interaction and multimedia learning theory. This system was implemented as a software-based intervention and evaluated with a pre-experimental one-group pretest–posttest design involving thirteen students with mild to moderate intellectual disabilities. Quantitative analysis included validity and reliability testing, paired samples t-test, effect size calculation, and normalized gain (N-gain) analysis. Results show significant improvement in reading literacy after the intervention. The N-gain score was high at 0.7038, and the effect size was very large, demonstrating strong educational effectiveness. These findings highlight the promise of computer-based animated video systems as effective, scalable technologies for inclusive education. The study offers a replicable framework for combining multimedia system design and quantitative evaluation in educational technology for learners with cognitive disabilities.