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Journal of Vocational, Informatics and Computer Education
Published by PT. Academic Bright Collaboration
ISSN : 29884918     EISSN : 29886325     DOI : https://doi.org/10.66053/voice
Core Subject : Science, Education,
Computer Science & IT Education
1. Informatics and Computing Research addressing the design, development, implementation, and evaluation of computing technologies relevant to educational, professional, and digital learning environments, including but not limited to: Artificial Intelligence and Machine Learning Deep Learning and Neural Networks Data Science, Big Data, and Data Analytics Software Engineering and Software Development Computer Networks and Internet Technologies Cloud Computing and Distributed Computing Systems Internet of Things (IoT) and Smart Systems Human–Computer Interaction (HCI) and User Experience (UX) Intelligent Systems and Decision Support Systems Natural Language Processing and Computational Applications Cybersecurity and Information Security Emerging Computing Technologies and Digital Systems 2. Information Technology in Education Studies focusing on the design, integration, implementation, and evaluation of digital technologies in teaching and learning environments, including: Computer Science Education and Programming Education Artificial Intelligence in Education (AIED) Educational Data Mining and Learning Analytics Intelligent Tutoring Systems and Adaptive Learning Systems Digital Learning Environments and Online Learning Systems Learning Management Systems (LMS) and E-learning Platforms Immersive Learning Technologies (Virtual Reality, Augmented Reality, Extended Reality) Mobile Learning and Ubiquitous Learning Environments Technology-Enhanced Learning (TEL) and Digital Pedagogy Educational Software and Learning System Development Digital Assessment and Technology-Based Evaluation Systems Computational Thinking, AI Literacy, and Digital Literacy in Education 3. Vocational Technology Education Research examining the integration of computing technologies and digital innovation in vocational, technical, and professional education, including: Curriculum Development in Informatics and Computing Education Competency-Based Training and Digital Skill Development Teaching Factory and Industry 4.0 Learning Environments Smart Learning Environments for Technical and Vocational Education Work-Process Knowledge and Workplace Learning Work-Based Learning and Apprenticeship Systems Industry–Education Collaboration in Computing and Technology Fields Workforce Preparation for Digital and Technology-Driven Industries Digital Literacy and Cybersecurity Education in Vocational Contexts Professional Skills Development for the Digital Economy 4. Innovative Digital Learning and Educational Innovation Research exploring innovative pedagogical approaches, emerging technologies, and new learning ecosystems in digital and technology-enhanced education, including: Innovative Digital Pedagogy and Instructional Design Gamification and Game-Based Learning in Computing and Technology Education Project-Based Learning and Problem-Based Learning Supported by Technology Learning Innovation Using Artificial Intelligence and Intelligent Systems Automation and Smart Learning Technologies in Education Digital Transformation in Education and Training Institutions Emerging Educational Technologies and Future Learning Environments Smart Education Ecosystems and Data-Driven Learning Systems Educational Innovation for Developing Digital Competencies and Future Skills
Arjuna Subject : Ilmu Sosial - Pendidikan
Articles 107 Documents
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A Learning Obstacle 11th-Grade Students in Solving Exponential Function Problems and Their Modeling Focus on Critical Thinking Skills Dwina Saptiani; Tatang Herman; Nanang Priatna
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.v4i1.876

Abstract

Purpose – This study aims to identify the learning obstacles experienced by eleventh-grade students when solving exponential function and modeling problems, particularly those related to critical thinking skills. Methods – A qualitative phenomenological approach was employed involving 30 eleventh-grade students. Data were collected through critical thinking tests, semi-structured interviews, textbook analysis, and focus group discussions. Students’ responses were categorized according to four critical thinking indicators: interpretation, analysis, evaluation, and inference. Findings – The results revealed several learning obstacles across the critical thinking indicators. Students had difficulty interpreting contextual situations, identifying relationships among variables, and understanding decay contexts. Errors in exponent operations and limited understanding of covariational relationships affected analytical reasoning. Students also struggled to predict function behavior without graphical representations and encountered difficulties in drawing conclusions or proposing alternative mathematical models. Research implications – The findings highlight the need for instructional designs that emphasize contextual reasoning, modeling activities, and action–formulation–validation processes to support critical thinking development. Originality – This study integrates critical thinking assessment with learning-obstacle analysis, providing a comprehensive explanation of the difficulties students encounter when solving contextual exponential function problems.
A Formally Specified Extension of RFC 9411 Benchmark Methodology for Sandbox-Based Advanced Threat Prevention in Next-Generation Firewalls Risqi Khoirun Nisa; Ruki Harwahyu
Journal of Vocational, Informatics and Computer Education Vol 4, No 2 (2026): June 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v4i2.892

Abstract

Purpose – This study proposes a formally specified, composable extension of RFC 9411 for benchmarking sandbox-based advanced threat prevention (ATP) in next-generation firewalls (NGFWs). It addresses four properties that the current standard cannot characterize: asynchronous verdict generation, file-level inspection granularity, bypass behavior under overload, and verdict latency as a security efficacy dimension.Methods – Following a design science methodology, the study develops a framework comprising a test traffic profile parameterized by file arrival rate (F), size distribution (s), type distribution (t), and maliciousness ratio (m); five formally defined key performance indicators (KPIs); a mapping table relating each component to its RFC 9411 counterpart; and a three-phase test procedure covering steady-state, overload, and recovery conditions. Empirical need is established through a vendor disclosure survey across three leading enterprise NGFW product lines.Findings – An illustrative scenario application, using plausible values rather than instrumented measurements, shows how the proposed KPIs would expose behaviors invisible to RFC 9411, such as a policy-driven bypass of 14% under a 30% traffic overload and a quantifiable trade-off between detection rate (α = 0.91–0.96) and verdict latency (p50 = 18–47 s). Empirically, a disclosure survey of three enterprise NGFW datasheets finds all five sandbox-specific KPIs absent from every datasheet, with composite disclosure indices of 23–34% and a cross-vendor mean of 28%. Research implications – The framework enables reproducible, comparable sandbox benchmarking and provides a normative basis for SLA design, evidence-based procurement, and IETF BMWG standardization.Originality – This study contributes the first formally specified, RFC 9411-composable benchmarking layer for sandbox-based ATP, introducing five new KPIs with mathematical definitions and a composability mapping table.
The Mediating Role of Digital Readiness in Human Capital Strategy and Employability Skills of Vocational Students Dwi Supriono; Erny Roesminingsih; Syunu Trihantoyo; Amrozi Khamidi; Mohammad Syahidul Haq
Journal of Vocational, Informatics and Computer Education Vol 4, No 2 (2026): June 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v4i2.932

Abstract

Purpose – This study examines the direct and indirect relationships among perceived Human Capital Strategy, Digital Readiness, and Employability Skills among vocational high school students. It also investigates whether Digital Readiness explains part of the relationship between students’ perceived educational development opportunities and employability-related competencies. Methods – A cross-sectional quantitative survey was conducted with 357 Grade XII students from six vocational high schools in Ponorogo Regency, Indonesia. Data were collected through a structured questionnaire. The proposed model was analyzed using Partial Least Squares Structural Equation Modeling in SmartPLS 4. The analysis included measurement-model assessment, structural-path estimation, explanatory power, predictive relevance, model fit, and mediation testing. Findings – Human Capital Strategy was positively associated with Employability Skills (β = 0.680, p < 0.001) and Digital Readiness (β = 0.841, p < 0.001). Digital Readiness was also positively related to Employability Skills (β = 0.208, p < 0.001). The indirect relationship through Digital Readiness was statistically significant (β = 0.175, p < 0.001). Because the direct path remained significant after the mediator was included, Digital Readiness was identified as a partial mediator. Research implications – Vocational schools should integrate digital capability development with occupational learning, workplace exposure, career preparation, and transferable-skill development. Digital readiness should therefore be strengthened as part of a broader human capital strategy rather than treated as a separate technology program. Originality – This study provides empirical evidence from Indonesian vocational education that Digital Readiness acts as a complementary pathway linking perceived human-capital-oriented educational experiences with Employability Skills.
Transforming Akidah Akhlak Teaching Materials into VCT-Based E-Modules for Character Internalization in the Digital Era: A Systematic Literature Review Ahmad Dimyati Ridwan; Syahidin; Mokh. Iman Firmansyah
Journal of Vocational, Informatics and Computer Education Vol 4, No 2 (2026): June 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v4i2.940

Abstract

Purpose – Digital disruption has escalated moral degradation, notably indiscipline and a diminished work ethic among Generation Z, while conventional Akidah Akhlak learning heavily relies on textual indoctrination. Therefore, this study examines the urgency of transforming printed materials into Value Clarification Technique (VCT)-integrated E-Modules to internalize the character values of discipline and hard work (ikhtiar).Methods – Using a Systematic Literature Review (SLR), 20 core articles were rigorously analyzed from an initial pool of 87 studies retrieved from Scopus, Sinta, and Garuda (2021–2026).Findings – Results highlight that VCT systematically transitions students from moral knowing to moral action. The proposed E-Module conceptualizes this transition through concrete pedagogical features: Digital Storytelling, Interactive Dilemma Boards, Private Journaling, and Action Trackers, corresponding to the VCT stages. Research implications – Ultimately, developing this VCT-based E-Module provides an evidence-informed design direction for madrasahs to cultivate resilient, high-integrity graduates.Originality – Although yet to be empirically tested, this architectural integration provides an evidence-informed conceptual framework to proactively counteract digital escapism.
Reinforcement Learning-Based Adaptive Threshold Optimization for Federated Sequence-to-Sequence Anomaly Detection in IoT Network Traffic Rahmad Hidayat Hadi Subroto; Kalamullah Ramli
Journal of Vocational, Informatics and Computer Education Vol 4, No 2 (2026): June 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v4i2.946

Abstract

Purpose – This study evaluates reinforcement learning (RL)-based adaptive threshold optimization for binary Internet of Things (IoT) network anomaly detection in a federated sequence-to-sequence (Seq2Seq) reconstruction model. Reconstruction-based detectors require a threshold to convert anomaly scores into benign-or-attack decisions, and a fixed threshold may not provide the most suitable operating point in federated non-IID settings.Methods – An LSTM Seq2Seq autoencoder was implemented using a controlled CICIoT2023 subset with 182,829 records and 39 numerical traffic features. Three scenarios were compared: centralized Seq2Seq with static threshold, federated Seq2Seq with static threshold, and federated Seq2Seq with RL-based adaptive threshold. Federated learning used five simulated clients, Dirichlet non-IID partitioning with α = 0.5, three local epochs, ten communication rounds, and weighted FedAvg aggregation. The RL component was implemented as an offline validation-based threshold optimizer and selected a single final threshold after federated training. Findings – Compared with federated static thresholding, the RL-based adaptive threshold improved accuracy from 92.97% to 95.71%, recall from 91.60% to 98.21%, and F1-score from 94.98% to 97.08%. FNR decreased from 8.40% to 1.79%, while FPR increased from 3.40% to 10.95%.Research implications – Threshold optimization should be treated as a decision-layer component in federated reconstruction-based IDS. The proposed pipeline may also support vocational informatics and cybersecurity education as a case study on federated learning, anomaly detection, and threshold-based IDS trade-offs.Originality – This study positions RL-based threshold adaptation as a decision-layer component in federated reconstruction-based IoT anomaly detection.
Implementation of Fingerprint Attendance to Improve the Accuracy of Student Attendance Data Palma Juanta; Felix; Verren A. Liandinata
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.v4i1.972

Abstract

Purpose – The use of manual attendance methods in educational environments often triggers operational obstacles, ranging from recapitulation errors to loopholes for attendance manipulation by students. Consequently, the resulting data validity is low, thus hampering the effectiveness of school administration. In response to this issue, this study implemented fingerprint scanning technology to ensure the accuracy and integrity of attendance information. This research was conducted to implement a fingerprint-based attendance system as a solution to improve the accuracy and reliability of student attendance dataMethods – Data were collected through observation, interviews, and documentation at the research location. The research process included the stages of designing, implementing, and directly testing the fingerprint attendance system. Data analysis was conducted using Simple Linear Regression Testing to measure the magnitude of the effect of the fingerprint attendance system implementation on improving the accuracy of student attendance data compared to the previously used manual system Findings – Statistical data analysis proved that the use of fingerprint technology significantly affected the accuracy of attendance reports at SMA Kristen Kalam Kudus 1 Medan. Based on SPSS calculations, Y = 26.771 - 0.301X was obtained, which indicates the relationship between the independent and dependent variables in this study. Research implications – The implementation of fingerprint attendance systems can serve as an effective technological innovation for enhancing the accuracy, reliability, and transparency of student attendance data management in educational institutionsOriginality – This study offers originality by specifically examining the role of fingerprint-based attendance systems in improving the accuracy of student attendance data through empirical analysis within an educational setting, an area that has received limited attention compared to studies focusing primarily on employee attendance management.
AI Assistant Use and Perceived Cognitive Skills in Programming: Extending the Technology Acceptance Model Fathahillah; Ayu Lestari; Muhammad Yahya; Muhammad Fardan; Putri Nanda Sari
Journal of Vocational, Informatics and Computer Education Vol 4, No 2 (2026): June 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v4i2.990

Abstract

Purpose - This study investigates the relationship between students’ use of AI assistants and their perceived cognitive abilities in programming by extending the Technology Acceptance Model (TAM) to incorporate perceived Computational Thinking (CT) and perceived Problem-Solving Skills (PSS).Methods - A quantitative survey was administered to 320 undergraduate students with prior experience using AI assistants for programming-related tasks. The data were gathered through a four-point Likert-scale questionnaire and subsequently analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS 4.Findings - The results showed that Perceived Usefulness was positively associated with Behavioral Intention to Use (β = 0.329, p < 0.001), while Perceived Ease of Use was positively associated with Perceived Usefulness (β = 0.680, p < 0.001) and Behavioral Intention to Use (β = 0.346, p < 0.001). Behavioral Intention to Use was positively associated with Actual Use (β = 0.741, p < 0.001). Actual Use was also positively associated with perceived CT (β = 0.672, p < 0.001) and perceived PSS (β = 0.754, p < 0.001).Research Implications - The findings suggest that AI assistants may support students’ perceived cognitive engagement in programming when used reflectively for debugging, comparing solutions, and understanding programming logic. However, the results should be interpreted as perceived cognitive support rather than objective evidence of cognitive skill improvement.Originality - This study extends TAM by linking AI assistant acceptance with perceived cognitive outcomes in AI-assisted programming.

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