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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 277 Documents
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Design and Evaluation of an Integrated Virtual Laboratory Framework with Learning Analytics for Vocational Computer Network Engineering Education Haida Dafitri; Abdul Hamid K; Sahat Siagian
Information Technology Education Journal Vol. 5, No. 2, May (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i2.266

Abstract

Purpose — This study proposes and evaluates an integrated virtual laboratory learning framework that combines virtual laboratories, Learning Management Systems (LMS), and learning analytics to support structured learning in vocational computer network engineering education. The framework is organized into five instructional phases (Highlight–Analyze–Integrate–Do–Assess) to facilitate coherent learning progression and data-informed feedback. Design/methods/approach — An early-stage (single-cycle) Design-Based Research (DBR) approach was employed using a quasi-experimental pre-test–post-test design involving 60 vocational high school students. Data were collected through cognitive achievement tests, practical performance assessments, classroom observations, and LMS-based learning analytics logs. Data analysis included normalized gain (N-gain), paired-sample t-tests, effect size (Cohen’s d), and descriptive and correlational analyses. Findings — The results indicate that the proposed framework is associated with improved cognitive achievement, with mean scores increasing from 58.3 to 82.7 (N-gain = 0.57). A statistically significant difference was found between pre-test and post-test scores (p < 0.001), with a large effect size (d = 1.34). In addition, 90% of students successfully completed virtual laboratory tasks. Learning analytics further revealed reduced error frequency, increased task efficiency, and more consistent engagement patterns over time. Research implications/limitations — Significant correlations were found between learning behaviors and outcomes, particularly task completion rate (r = 0.52). However, due to the absence of a control group, the single-institution context, and the early-stage DBR design, the findings should be interpreted as indicative rather than causal, limiting generalizability. Originality/value — This study contributes by demonstrating how virtual laboratories, LMS, and learning analytics can be systematically aligned within a structured instructional framework in vocational education. The study emphasizes pedagogical sequencing and the integration of behavioral analytics into the learning process, providing initial empirical support for technology-enhanced instructional design that warrants further validation through multi-site and longitudinal studies.
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.
IoT-Based Road Blackspot Detection via GPS and Web Integration: Design, EAN-Based Risk Classification, and Field Evaluation Ghani Ridho Rahmatullah; Mokhammad Rifqi Tsani; Raka Pratindy; Siti Shofiah
Information Technology Education Journal Vol. 5, No. 2, May (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i2.267

Abstract

Purpose – Road safety on high-traffic inter-city corridors in Indonesia remains a pressing concern, as drivers receive no real-time hazard notification when approaching zones with statistically elevated crash history. This study develops and evaluates an ESP32-based early warning system that couples GPS-derived positioning with the Equivalent Accident Number (EAN) method to issue graduated audio-visual alerts at road blackspots along the Palur–Semarang bus corridor. Design –  EAN quantifies accident severity by weighting fatalities (12), serious injuries (3), minor injuries (1), and property-damage incidents (0.5); segments exceeding the Upper Control Limit (UCL = 170,52) are designated blackspots, with coordinates stored in onboard flash memory. A SIM800L GPRS module transmits positioning data to a web-based fleet monitoring dashboard. Findings – Field evaluation across 10 GPS sampling points yielded mean errors of 0.00033% for latitude (3.7 m) and 0.00005% for longitude (5.0 m), with maximum deviations of 8.9 m and 17.8 m—both within the 800 m geofencing radius. All 10 from 64 validated corridor zones returned EAN values of 199,5–668,5, each exceeding the UCL, with web-platform outputs matching manual calculations exactly. Eight integrated test scenarios confirmed three-tier audio-visual alert delivery at 800 m, 400 m, and 100 m thresholds with zero missed triggers and zero spurious activations. Research implications – These findings provide preliminary evidence for the technical feasibility of EAN-based blackspot intelligence as a driver vigilance aid; however, full-route longitudinal testing across diverse vehicles and network conditions is required before generalised deployment can be recommended. Originality – This study integrates EAN-based crash severity analysis with real-time GPS tracking in an ESP32 system to deliver tiered early warnings for road blackspots.  
Development of a YOLO- and MQTT-Based Overtaking Warning System for Intelligent Driver Safety Education Muhammad Faris Haidar; Helmi Wibowo
Information Technology Education Journal Vol. 5, No. 2, May (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i2.269

Abstract

Purpose – This study aims to develop an intelligent overtaking warning system based on YOLOv8 object detection and Vehicle-to-Vehicle (V2V) communication using MQTT, designed as a prototype with the potential to serve as an interactive learning medium for driver safety and vehicular communication concepts. The study is motivated by the limited availability of practical educational tools for understanding overtaking processes and real-time communication in the Internet of Vehicles (IoV) context. Design – The research adopts a research and development (R&D) approach, including system design, implementation, and testing stages. The system is built using Raspberry Pi and ESP32, integrating GPS and LiDAR sensors with OCR-based recognition, and is evaluated through technical performance testing and user perception analysis using a Likert-scale questionnaire with validity and reliability testing. Findings – The results show that the system achieves an average end-to-end detection and processing delay of 0.911 seconds, while MQTT communication latency averages approximately 0.1269 seconds under controlled network conditions, with stable bidirectional communication. The YOLOv8 model performs optimally at a confidence threshold of 0.4, and the GPS and LiDAR sensors produce average error rates of 3.99% and 2.86%, respectively, while MQTT communication achieves a 100% success rate under tested conditions. Questionnaire results indicate that respondents reported positive perceptions regarding system usefulness, with most questionnaire items meeting validity criteria (r > 0.31) and a Cronbach’s Alpha of 0.952, indicating high reliability. Research Implication – These findings suggest that the system is technically feasible and demonstrates perceived educational potential as an interactive learning medium. However, this study is limited by the number of respondents and simulation-based testing; therefore, future work should include real-world traffic testing and larger-scale evaluations to improve system robustness and applicability. Originality – This study integrates YOLOv8-based object detection with MQTT-based V2V communication to develop an intelligent overtaking warning system as an interactive learning medium in IoV contexts.
Development of Virtual Reality Learning Media Assisted by Millealab for Islamic History Education in Secondary School Pandu Hyangsewu; Muhamad Ridwan Sudaryat; Achmad Faqihuddin; Aulia Tegar Wicaksono; Rosmalizawati Ab Rashid
Information Technology Education Journal Vol. 5, No. 2, May (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i2.261

Abstract

Purpose – This study aims to develop and test the feasibility and practicality of a virtual tour learning media assisted by the Millealab platform for Islamic history material on the Ottoman Empire at one of the SMP in Bandung. Design/methods/approach – This study uses a Research and Development (R&D) design through the procedural ADDIE model approach (Analysis, Design, Development, Implementation, and Evaluation). Sampling was conducted using a random sampling technique involving 167 students for needs analysis and 30 students for field implementation. Data collection instruments included expert validation sheets and practicality assessment questionnaires. Findings – The results showed that the virtual tour product achieved "Highly Valid" criteria with scores of 89.50% from material experts and 92.30% from media experts. Field trials recorded "Highly Practical" criteria with 88.00% from educators and 88.40% from students Research implications/limitations – The scope of this study is strictly limited to the Ottoman Empire material and small-scale practicality testing. Functionally, this innovation is proven to bridge the technical barriers of educators in producing virtual reality content without requiring programming skills. Originality/value – This research provides a practical framework regarding the utilization of a no-code virtual reality platform within the domain of Islamic history education, an area that is still rarely examined operationally.
Expert System for Bus Vehicle Failure Diagnosis Using the Decision Tree Method: A Web-Based Approach for Operational Fleet Management Raga Nur Iman Pribadi; Mokhammad Rifqi Tsani; Gunawan; Faris Humami
Information Technology Education Journal Vol. 5, No. 2, May (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i2.270

Abstract

Purpose – This study aims to develop a web-based expert system to support initial fault identification in bus fleets, addressing the limitations of manual, experience-based diagnostics that are often subjective and time-consuming in operational environments. Design/methods/approach – The system was developed using a rule-based approach with a Decision Tree framework, where entropy and information gain were used to structure expert knowledge into an interpretable diagnostic hierarchy. The development followed the SDLC Waterfall model and incorporated 30 fault categories across six subsystems. Validation included entropy-based computation on the AC subsystem and expert-scenario testing across all subsystems (90 cases). System usability was evaluated using the System Usability Scale (SUS), and functional testing was conducted using Black Box Testing. Findings – The system achieved an accuracy of 97.78% under expert-defined diagnostic scenarios. However, this result reflects rule-consistency performance within structured scenarios and should not be interpreted as real-world diagnostic accuracy. The SUS evaluation yielded a score of 82.07, categorized as “excellent,” and all functional modules operated correctly based on Black Box Testing.Research limitations/implications – The validation is based on expert-defined scenarios rather than independently observed operational failure data, limiting generalizability. In addition, overlapping symptoms may introduce ambiguity in certain diagnostic conditions. Originality/value – This study contributes an interpretable expert system that integrates entropy-based attribute prioritization within a web-based fleet management context, providing structured diagnostic support for non-technical operational personnel.
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.
The Influence of AI Literacy on the Intention to Use Generative AI in Learning: The Mediating Role of Perceived Usefulness and Moderating AI Anxiety Zainal Syahlan; Leli Setyaningrum; Isnadi; Hadi Mardiyanto
Information Technology Education Journal Vol. 5, No. 2, May (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i2.272

Abstract

Purpose – This study aims to examine the influence of AI Literacy on students’ Intention to Use Generative AI in learning activities through the mediating role of Perceived Usefulness and the moderating role of AI Anxiety within the higher education context. Design/methods/approach – The study employed a quantitative explanatory approach using a cross-sectional survey design. Data were collected from 250 university students who had prior experience using generative AI for academic purposes. Respondents were selected through purposive sampling based on predefined inclusion criteria. The research instrument consisted of structured questionnaire items measured using a five-point Likert scale. Data analysis was conducted using Structural Equation Modeling–Partial Least Squares (SEM-PLS) to evaluate the measurement model, structural relationships, mediation effect, and moderation effect among variables. Findings – The results indicate that AI Literacy significantly influences both Perceived Usefulness and Intention to Use Generative AI. Perceived Usefulness was also found to positively affect behavioral intention and partially mediate the relationship between AI Literacy and Intention to Use. Furthermore, AI Anxiety negatively moderated the relationship between Perceived Usefulness and Intention to Use, suggesting that psychological concerns toward AI weaken students’ willingness to adopt generative AI despite recognizing its educational benefits. Research implications/limitations – This study contributes to the development of AI-based technology acceptance research by integrating cognitive and psychological factors into a single analytical framework. However, the use of a cross-sectional design and self-reported data may limit the generalizability and causal interpretation of the findings. Originality/value – The originality of this study lies in the integration of AI Literacy, Perceived Usefulness, and AI Anxiety within the Technology Acceptance Model to explain generative AI adoption behavior in higher education learning environments.
Hull Design Optimization and Ship Resistance Reduction: The Mediating Role of Hydrodynamic Performance and the Moderating Effect of Ship Speed ​​Variation Wawan Kusdiana; Ardiansyah; Cahya Kusuma; Anton Nugroho; Jajang Amir Hidayat
Information Technology Education Journal Vol. 5, No. 2, May (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i2.273

Abstract

Purpose –This study investigates the relationships among Hull Design Optimization (HDO), Hydrodynamic Performance (HP), Ship Resistance Reduction (SRR), and Ship Speed Variation (SSV) within an integrated mediation–moderation framework. Specifically, the study examines the direct effects of hull design optimization on hydrodynamic performance and ship resistance reduction, the mediating role of hydrodynamic performance, and the moderating effect of ship speed variation. Design/methods/approach – A quantitative explanatory research design was employed using a survey of 180 maritime professionals, including naval architects, shipyard engineers, hydrodynamic researchers, ship surveyors, consultants, lecturers, and graduate students. Data were collected through a structured questionnaire and analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS). Findings – The results indicate that Hull Design Optimization has a significant positive effect on Hydrodynamic Performance (β = 0.910, p < 0.001) and Ship Resistance Reduction (β = 0.445, p < 0.001). Hydrodynamic Performance significantly influences Ship Resistance Reduction (β = 0.347, p = 0.001) and partially mediates the relationship between Hull Design Optimization and Ship Resistance Reduction (β = 0.316, p = 0.001). Furthermore, Ship Speed Variation significantly moderates the relationship between Hydrodynamic Performance and Ship Resistance Reduction (β = 0.135, p < 0.001). The structural model demonstrates substantial explanatory and predictive power. Research implications/limitations – The findings emphasize the importance of integrating hydrodynamic considerations and operational speed conditions into ship design optimization strategies. However, the study relies on expert perceptions and a cross-sectional survey design, which may limit the generalizability of the findings to actual vessel operations. Originality/value – This study contributes to the maritime engineering literature by integrating mediation and moderation mechanisms within a single SEM-PLS framework, providing a more comprehensive explanation of how hull optimization influences ship resistance reduction through hydrodynamic performance under varying operational speed conditions.

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