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All Journal Information Technology Education Journal Jurnal Pengabdian Masyarakat dan Riset Pendidikan Journal of Vocational, Informatics and Computer Education
Masna, Ummul Khaeri
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Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Other

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Pemberdayaan UMKM melalui Literasi Kecerdasan Buatan dan Teknologi Augmented Reality untuk Transformasi Ekosistem Kewirausahaan Digital di Kelurahan Masale Kota Makassar: Penelitian Amraeni, Amraeni; Alisyahbana, Andi Naila Quin Azisah; Mushaf, Mushaf; Syukur, Pramudya Asoka; Masna, Ummul Khaeri; Andri, Dian Puspita Sari; Isma, A; Dewantara, Hajar
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 2 (2025): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 2 (October 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i2.3543

Abstract

The low level of digital adoption among Micro, Small, and Medium Enterprises (MSMEs), particularly in tax administration and marketing, continues to hinder competitiveness. This community service program focuses on empowering MSMEs in Masale Sub-district, Makassar City through Artificial Intelligence (AI)-based tax literacy and the use of Augmented Reality (AR) for digital promotion. The activity aims to enhance MSME capacity through AI literacy training for tax management and the application of AR in digital marketing strategies. The method used is Participatory Action Research (PAR), implemented through socialization, smart tax and AR content creation training, mentoring, and evaluation using pre-test and post-test. The results show a significant improvement, with the average accuracy increasing from 48.2% in the pre-test to 91.8% in the post-test. This program effectively strengthens MSMEs’ digital skills, improves operational efficiency, and expands AR-based promotional reach, all of which contribute to building a sustainable digital entrepreneurship ecosystem.
Extending the Technology Acceptance Model (TAM) to Predict Student Learning Outcomes in GNS3 Based Networking Education Masna, Ummul Khaeri; Salim, Agus; Ramadani, Fitra; Baso, Fadhlirrahman
Information Technology Education Journal Vol. 5, No. 1, February (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i1.265

Abstract

Purpose – This study investigates the factors influencing network simulator acceptance and its direct impact on learning outcomes within the Department of Informatics and Computer Engineering. It addresses the gap between technology adoption and actual academic success in a technical vocational context. Design/methods/approach – A quantitative approach using the Technology Acceptance Model (TAM) was applied. Data from 187 students were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4.0, employing a 5,000-resample bootstrapping procedure. Findings – Results confirm that Perceived Usefulness significantly drives Behavioral Intention (β= 0.774, p < 0.001), while Perceived Ease of Use is non-significant (β = 0.150, p = 0.166). Crucially, Behavioral Intention strongly predicts Learning Outcomes (β = 0.849, p < 0.001). The model exhibits substantial predictive power, explaining 83% of the variance in intention (R2 = 0.830) and 72.1% in learning outcomes (R2 = 0.721). Research implications/limitations – Engineering pedagogy should prioritize demonstrating the industrial utility of simulators over interface simplicity. Limitations include the cross-sectional design and reliance on self-reported data within a single department, which may affect generalizability. Originality/value – This research empirically bridges technology acceptance with tangible academic performance in the Indonesian technical education context. It provides a validated framework for enhancing technical competencies through strategic tool integration.
The Concern Over Brain Rot from Generative AI Use Among Preservice Teachers: A UTAUT Approach Masna, Ummul Khaeri; Sidin, Udin Sidik; Mushaf; Stephen Amukune
Journal of Vocational, Informatics and Computer Education Vol 4, No 1 (2026): March 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v4i1.347

Abstract

Purpose – The increasing use of generative AI on campus has raised concerns about a potential decline in students’ critical thinking skills. While the UTAUT theory is widely used to examine technology adoption, its relationship with the phenomenon of brain rot remains underexplored, particularly among preservice teachers. This study aims to analyze the factors associated with preservice teachers’ intention to use generative AI within the UTAUT framework, as well as to examine its association with tendencies toward brain rot.Method – A quantitative cross-sectional design was conducted with 243 preservice teachers from Universitas Negeri Makassar. Data were collected via a validated 30 item questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the relationships between technology adoption constructs and brain rot tendencies.Findings – Social influence was the only significant predictor of behavioral intention to use AI (β = 0.269, p = 0.002). Behavioral intention, in turn, showed a strong positive association with brain rot tendencies (β = 0.817, p < 0.001), explaining 66.7% of the variance (R² = 0.667). Other UTAUT constructs, including performance expectancy and effort expectancy, were not significant predictors. However, given the cross-sectional design, these findings reflect statistical associations rather than causal relationships.Research Implication : Socially driven AI adoption is strongly linked to cognitive passivity, highlighting the need to extend UTAUT with cognitive risk factors and rethink how technology use impacts higher-order thinking.Conclusion – This study indicates that the adoption of AI among preservice teachers is associated with perceptions of declining cognitive abilities. These findings highlight the importance of promoting critical AI literacy and developing assessment approaches that emphasize deep cognitive engagement. Future research is recommended to employ longitudinal designs or incorporate control variables such as digital self-efficacy.
Co-Authors Agus Salim Alisyahbana, Andi Naila Quin Azisah Amraeni, Amraeni Andri, Dian Puspita Sari Arum Putri Rahayu Baso, Fadhlirrahman Hajar Dewantara Isma, A Mawaddah, Sakinah Muh. Yusril Anam Mushaf Mushaf, Mushaf Nurrahmah Agusnaya Ramadani, Fitra Stephen Amukune Syukur, Pramudya Asoka Udin Sidik Sidin