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M. Miftach Fakhri
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Information Technology Education Journal
Published by Universitas Negeri Makassar
ISSN : 28097971     EISSN : 2809798X     DOI : -
Core Subject : Science, Education,
Computer Science & IT Education
INTEC Journal is published by the Informatics and Computer Engineering Education Study Program at Makassar State University. INTEC Journal is published periodically three times a year, containing articles on research results and / or critical studies in the field of Informatics and Computer Engineering Education from students, lecturers, and practitioners from universities or research institutions. The INTEC journal already has a print version ISSN with the number 2809-798X in 2022 and an online version ISSN with the number 2809-7971. INTEC Journal contains articles on informatics and computer engineering education in particular: learning multimedia e-learning/blended learning, information system, artificial intelligence and robotics, embedded expert system, big data and machine learning, software and network engineering
Arjuna Subject : Ilmu Sosial - Pendidikan
Articles 8 Documents
 1 
Search results for , issue "Vol. 5, No. 1, February (2026)" : 8 Documents clear
Maturity Assessment at a University IT Center Using COBIT 2019 EDM and APO Domains Zufria, Ilka; Muhammad Siddik Hasibuan
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.v5i1.262

Abstract

Purpose – This study evaluates the capability of IT governance at Pustipada UIN Sumatera Utara Medan to determine whether current technology practices are aligned with institutional strategic objectives, particularly in terms of resource optimization, governance structure, and innovation. The study addresses the gap between existing governance performance and expected capability levels within higher education institutions.  Design – A descriptive qualitative design was employed. Data were collected through in-depth interviews with key stakeholders identified using RACI Chart mapping, analysis of SOP and KPI strategic documents, and direct observation of objective alignment. The evaluation focused on selected COBIT 2019 domains, namely EDM04 (resource optimization), APO01 (management framework), and APO04 (innovation).  Findings – The results indicate that the EDM04 domain achieved a capability level of 3 with a score of 2.24, below the expected level 4 (2.60), resulting in a gap of 0.36. The APO01 domain also reached level 3, indicating moderate maturity in governance structure, while the APO04 domain recorded a lower score of 1.58, reflecting weak innovation governance. These findings confirm that IT governance implementation remains suboptimal and requires systematic improvement.  Research implications – The study is limited to a single institutional context, which restricts generalizability. The reliance on qualitative data and the absence of integrated financial SOPs may also affect the comprehensiveness of governance evaluation and limit deeper performance validation.  Originality – This research provides a quantified baseline of IT governance capability within a higher education context in North Sumatra, offering actionable insights and strategic recommendations, particularly in formalizing resource documentation and strengthening governance processes as a roadmap for similar institutions.
Utilizing AI in Digital Learning: The Role of Metacognitive Reasoning, Organizational Support, and Socioeconomic Status in Enhancing Academic Performance through Intrinsic Motivation Awalia, Andi Dio Nurul; Rosidah; M.Miftach Fakhri; Della Fadhilatunisa
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.v5i1.261

Abstract

Purpose – This study examines how metacognitive reasoning, organizational support, and socioeconomic status shape academic performance through the mediating role of intrinsic motivation in an artificial intelligence (AI) integrated learning environment. Design – A quantitative, cross-sectional design was employed. Data from 373 university students were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate relationships among the constructs. Findings – Metacognitive reasoning and organizational support significantly increased intrinsic motivation, which in turn positively affected academic performance. By contrast, socioeconomic status did not significantly influence intrinsic motivation or academic performance. Research implications – The results underscore the importance of cognitive and contextual supports in fostering student motivation and achievement. The nonsignificant effects of socioeconomic status warrant further investigation; future studies should explore additional individual and environmental factors that may shape academic outcomes in AI-enabled learning settings. Originality –  This research advances an inclusive and effective framework for digital learning in higher education by demonstrating the central role of metacognitive skills and institutional support in designing AI-enhanced strategies that cultivate students intrinsic motivation and academic success.  
Determinants of Learning Effectiveness in Digital STEM Higher Education: A Cross-Sectional Study Using Hierarchical Regression Fresa Dwi Juniar Sofalina; Rudi Priadi; M. Iqbal Faiz
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.v5i1.263

Abstract

Purpose - This study examines the determinants of learning effectiveness in digital STEM higher education, focusing on Technology Integration in Management (TIM), Digital Monitoring and Evaluation (DME), and Organizational Digital Support (ODS) within an institutional context. Design - A quantitative explanatory study with a cross-sectional survey was conducted among undergraduate students (n = 260) at a private higher education institution in Bandung, Indonesia, who had experienced online or blended learning. Hierarchical multiple regression was used to assess the incremental explanatory power of TIM, DME, and ODS beyond control variables (gender, study year/semester, LMS usage intensity, and internet stability). Findings - The control model explained 14% of the variance in learning effectiveness (R² = 0.14). After including TIM, DME, and ODS, the explained variance increased to 54% (R² = 0.54; ΔR² = 0.40). DME was the strongest predictor (β = 0.33), followed by TIM (β = 0.24) and ODS (β = 0.18), all of which showed significant positive effects. The results highlight the critical role of structured monitoring, continuous evaluation, and coherent management of digital learning processes in enhancing student performance. Research implications - Enhancing digital learning effectiveness requires strengthening data-informed monitoring systems, structured LMS-based learning management, and consistent institutional support. However, the findings are limited to a single institutional context and cross-sectional design; future studies should use longitudinal and multi-institutional data. Originality/value - This study integrates technology management, evaluation practices, and organizational support into a unified digital learning governance model, providing context-specific empirical evidence from Indonesian higher education.
Fear of Cyberattacks and Measure Efficacy among Students in Higher Education: The Sequential Roles of Perceived Severity and Perceived Vulnerability Sofyan, Vina Annisa; Khaira Ummah; Mushaf
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/vgpe6v78

Abstract

Purpose – This study examines the effect of fear of cyberattacks on measure efficacy among students in higher education and investigates the sequential roles of perceived severity and perceived vulnerability. Design/methods/approach – A quantitative approach was employed using an online survey of 203 university students selected through purposive sampling. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings – The results show that fear of cyberattacks significantly influences perceived severity (β = 0.754, t = 13.487, p < 0.001), perceived severity significantly influences perceived vulnerability (β = 0.295, t = 4.374, p < 0.001), and perceived vulnerability significantly influences measure efficacy (β = 0.310, t = 4.613, p < 0.001). In addition, perceived vulnerability significantly mediates the relationship between perceived severity and measure efficacy (β = 0.091, t = 2.469, p = 0.014), while perceived severity and perceived vulnerability jointly mediate the relationship between fear of cyberattacks and measure efficacy (β = 0.069, t = 2.189, p = 0.029). Research implications/limitations – The study is limited by its cross-sectional design, self-reported responses, and focus on university students. However, the findings suggest that cybersecurity education in higher education should strengthen students’ understanding of threat severity and personal vulnerability to improve protective efficacy. Originality/value – This study contributes to information technology education by extending Protection Motivation Theory to explain how emotional and cognitive processes shape students’ protective efficacy in digital environments.
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.
FORCAS: A Least Squares-Based Forecasting Application for Business Sales Budgeting Bakhtiar, Yohan; Abidatul Izzah; Ahmad Saifi Athoillah; Dion Yanuarmawan; Wiwik Mukholafatul Farida; Dwi Rahma Fitriani
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.v5i1.266

Abstract

Purpose – This study aims to develop FORCAS (Forecasting Comprehensive Application for Sales), a universal forecasting application based on the Least Squares method to support business sales budgeting.  Design – The research employed a system development approach consisting of problem analysis, system design, algorithm implementation, and application testing. The Least Squares method was used to generate sales forecasts, while system validation was conducted through black box testing. User experience and usability were evaluated using the System Usability Scale (SUS) and User Experience Questionnaire (UEQ).  Findings – The results show that FORCAS successfully generates accurate sales forecasts consistent with manual Least Squares calculations. Black box testing confirmed that all system functions operated correctly. Usability evaluation yielded a SUS score of 71, indicating a Grade C (acceptable usability), while UEQ results showed an Excellent rating across pragmatic and hedonic dimensions. Research implications – In conclusion, FORCAS provides a practical and replicable forecasting tool that can be applied across various business contexts. The application is particularly beneficial for small and medium enterprises (SMEs) and accounting education, offering an accessible solution for systematic sales budgeting. Future development may include the integration of advanced forecasting models such as ARIMA and machine learning-based methods.  Originality – However, most existing forecasting systems are designed for specific cases and lack flexibility for broader business applications. This study develops FORCAS as a universal forecasting application to address this limitation.
A Bibliometric Analysis of Research Trends on Smartphone Use in Early Childhood (2011–2024) Hasanah, Uswatun; Khilmiyah, Akif; M. Suud , Fitriah
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.v5i1.268

Abstract

Purpose - This study aims to examine the development and research trends related to smartphone use among young children through a bibliometric analysis of scientific publications. Design - This study employed a bibliometric approach by analyzing 220 Scopus-indexed journal articles published between 2011–2024 using Biblioshiny and VOSviewer. The analysis focused on publication trends, dominant themes, collaboration patterns, and research developments within the field. Findings - The results indicate a significant increase in scientific attention to smartphone use among young children since 2011, particularly within education, psychology, and health-related disciplines. Dominant research themes include screen time, child development, behavioral impacts, and parental mediation. The United States, the United Kingdom, and China were identified as the most productive countries in this research field. Emerging topics such as artificial intelligence and digital learning also indicate the expansion of technology-oriented perspectives in early childhood research. Research implications - The findings provide a structured overview of research developments related to smartphone use in early childhood and may support future studies, educational practices, and policy development concerning children’s digital environments. Originality/value - This study offers a systematic bibliometric perspective on smartphone use in early childhood by mapping publication trends, thematic developments, and collaboration patterns from 2011–2024.
Explaining Students’ Continuance Intention to Use Artificial Intelligence in Higher Education: A Post-Adoption TAM Model Faiz, Muhammad Nur; Muhammad Yahya; Rosidah; Sanatang
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.v5i1.267

Abstract

Purpose – This study examines continuance intention to use artificial intelligence in higher education by integrating system quality, self efficacy in artificial intelligence usage, and artificial intelligence literacy into a post adoption technology acceptance framework. The study clarifies whether sustained use is driven more by technical and usability related evaluations than by literacy alone. Design/methods/approach – A quantitative cross sectional survey was conducted with 324 undergraduate students from the Informatics and Computer Engineering Education and Computer Engineering study programs at Universitas Negeri Makassar. Data were collected through an online questionnaire and analyzed using Partial Least Squares Structural Equation Modeling with SmartPLS 4. Findings – Self-efficacy in artificial intelligence usage significantly affected artificial intelligence literacy (β = 0.447, p < 0.001), system quality significantly affected perceived ease of use (β = 0.733, p < 0.001) and perceived usefulness (β = 0.266, p < 0.001), perceived ease of use significantly affected perceived usefulness (β = 0.502, p < 0.001), and perceived usefulness significantly affected continuance intention (β = 0.637, p < 0.001). Artificial intelligence literacy did not significantly affect perceived usefulness (β = 0.072, p = 0.093). Research implications/limitations – The findings are limited by the cross-sectional design, self-reported data, and the focus on two technology-oriented study programs in one university. Originality/value – This study contributes a focused post-adoption explanation of sustained artificial intelligence use by showing that continuance is shaped more strongly by system performance and perceived academic value than by artificial intelligence literacy alone.

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