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M. Miftach Fakhri
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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 88 Documents
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The Impact of Digital Pattern Making-based Learning on Pattern Accuracy and Production Efficiency in Vocational Fashion Education Nurhijrah; Wabdillah
Journal of Vocational, Informatics and Computer Education Vol 3, No 2 (2025): December 2025
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v3i2.745

Abstract

This study examined the effectiveness of digital pattern-making-based instruction in improving students’ pattern accuracy and production efficiency in vocational fashion education. The study specifically addressed the limited empirical evidence concerning the simultaneous evaluation of technical precision and workflow efficiency within vocational secondary school contexts in Indonesia. A quasi-experimental pretest–posttest control group design was employed involving 60 eleventh-grade students enrolled in the Fashion Design Program at SMK Negeri 8 Makassar, Indonesia. The participants were divided into an experimental group (n = 30) and a control group (n = 30). The experimental group received instruction using CAD-based digital pattern-making software (CLO 3D), while the control group received conventional manual pattern-making instruction. Data were collected using a performance assessment rubric and a structured time-recording instrument. The rubric evaluated measurement accuracy, pattern completeness, line consistency, and adherence to design specifications. Content validity was established through expert judgment involving vocational education specialists and fashion industry practitioners, while reliability testing produced a Cronbach’s Alpha coefficient of 0.89, indicating high internal consistency. The findings revealed that students who received digital instruction achieved significantly higher pattern accuracy (M = 84.72, SD = 5.21) than students in the control group (M = 71.36, SD = 6.03), t(58) = 9.18, p < 0.001, with a very large effect size (Cohen’s d = 5.63). The experimental group also demonstrated significantly higher production efficiency (M = 65.40 minutes) compared with the control group (M = 82.15 minutes), t(58) = -9.18, p < 0.001, with a large practical effect (Cohen’s d = 2.37). These findings indicate that digital pattern-making instruction effectively enhances technical competency and workflow efficiency in vocational fashion education.
Female Representation in Vocational High School Leadership and Organizational Productivity: A Narrative Study of Women Principals in Gender-Associated School Environments in West Java, Indonesia Rizki Satria Nugraha; Aan Komariah; Taufani Chusnul Kurniatun; Abubakar Abubakar; Sururi Sururi
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

Abstract

This study examines how female representation in vocational high school leadership contributes to organizational productivity in gender-associated school environments in West Java, Indonesia. Grounded in the argument that leadership diversity is not only an equality concern but also an institutional resource, the study employed a qualitative narrative approach. Data were collected through semi-structured narrative interviews with six female principals from vocational high schools whose organizational settings were marked by gendered assumptions in fields such as mechanics, automotive, and patisserie. The findings reveal three central themes: leadership legitimacy as a condition for institutional productivity, adaptive relational leadership as a mechanism of organizational coordination, and female leadership as a contributor to school productivity through trust, discipline, communication, and program continuity. The study concludes that female representation in school leadership should be understood not merely as symbolic inclusion, but as a productive pathway toward more responsive, coordinated, and effective educational organizations in contemporary Indonesia.
Gamification on LMS and Learning Motivation in German Grammar: An ARCS-Based Study in Indonesian Higher Education Ambo Dalle; Johar Amir; Alamsyah; Sabrina Saiidi; Alissa Geisler
Journal of Vocational, Informatics and Computer Education Vol 3, No 2 (2025): December 2025
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v3i2.842

Abstract

Purpose – This study investigates the association between implementing gamification elements in a Learning Management System (LMS) and students' learning motivation in a German Grammar (Grammatik) course. Low learning motivation in repetitive and complex grammar instruction constitutes the primary background of this research. Methods – The study employed a one-group pretest-posttest quasi-experimental design involving 30 students enrolled in the German Language Education Study Program. Data were collected using a Motivation Scale based on the ARCS model (Attention, Relevance, Confidence, Satisfaction) comprising 20 items on a five-point Likert scale. Data analysis utilized the Wilcoxon Signed-Rank test and N-Gain score. Findings – A statistically significant improvement in learning motivation was observed following gamification implementation (Z = −4.782; p < 0.001; r = 0.87). The mean score increased from 63.13 (pretest) to 81.00 (posttest). Progress Bar (mean satisfaction = 4.63) and Points (4.52) received the highest student satisfaction ratings among the five implemented gamification elements. Research implications – Limitations include a small sample size (n = 30) from a single institution, a one-group design without a control group, and an intervention duration limited to one semester. Generalization of findings should be exercised with caution. Originality – This study represents one of the first empirical investigations of gamification within an institutional LMS in the context of German Grammar instruction in Indonesian higher education, developing an ARCS-based motivation instrument adapted for the Deutsch als Fremdsprache (DaF) context.
Heuristic Evaluation of German Language Mobile Learning Applications Among Indonesian University Students Syarifah Fatimah; Muftihaturrahmah Burhamzah; Alamsyah; Sabrina Saiidi
Journal of Vocational, Informatics and Computer Education Vol 3, No 2 (2025): December 2025
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v3i2.843

Abstract

Purpose – Despite the growing availability of German language mobile learning applications, no empirical usability evaluation targeting Indonesian university students enrolled in German Language Education study programmes has been reported. This study evaluates the usability of three mobile applications used in German language learning two commercial apps and one campus-developed app using Nielsen's (1994) heuristic evaluation framework. Methods – A heuristic evaluation was conducted by 25 student evaluators trained in Nielsen’s ten usability heuristics. Each evaluator independently rated usability problems on a 0–4 severity scale across three apps: Duolingo (App A), Babbel (App B), and a campus-developed mobile LMS (App C). Evaluators also completed the System Usability Scale (SUS). Data were analysed using descriptive statistics and the Friedman test with Wilcoxon signed-rank post-hoc comparisons (α = .05), appropriate for the repeated-measures design in which the same 25 evaluators assessed all three applications.  Findings – The campus app (App C) yielded the highest overall mean severity score (2.09) with 90 usability problems identified, predominantly in the Minor to approaching-Major severity range (mean scores 1.5–2.8 on Nielsen’s 0–4 scale). The most severe violations involved Help and Documentation (H10: M = 2.8) and Flexibility and Efficiency of Use (H7: M = 2.6). SUS scores were: App A = 82.4 (Good), App B = 74.8 (Good), App C = 51.6 (OK). Within-evaluator differences across the three applications were statistically significant for both severity (Friedman χ²(2) = 38.42, p < .001, W = .77) and SUS (Friedman χ²(2) = 34.88, p < .001, W = .70), with large effect sizes. Research implications – Findings are limited by the use of trained student evaluators rather than expert usability professionals, a single-institution sample, and the absence of summative user testing with actual German language learning tasks. The simulated evaluation context may not capture all real-world interaction patterns. Originality – This study is the first to apply Nielsen's heuristic evaluation framework to German language mobile learning applications in the Indonesian higher education context. It provides an empirically grounded usability problem list and design recommendations specifically relevant to campus-developed German language learning apps, contributing to both HCI research and German language education technology practice.
The Effect of Indonesian-Language Chatbot Interface Design on User Experience in an Academic Writing Practice Platform in Higher Education Johar Amir; Ambo Dalle; Alamsyah; Sabrina Saiidi
Journal of Vocational, Informatics and Computer Education Vol 3, No 2 (2025): December 2025
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v3i2.844

Abstract

Purpose – Academic writing proficiency remains a persistent challenge for university students in Indonesia. This study investigates whether differences in the user interface (UI) design of an Indonesian-language chatbot - specifically a formal/minimalist design versus a conversational/feature-rich design - produce significant differences in user experience (UX) within an academic writing practice platform at the higher education level. Methods – A quasi-experimental design was employed with 30 undergraduate students divided into two groups of 15. Participants interacted with their assigned chatbot interface across four writing sessions. Data were collected using the System Usability Scale (SUS), the User Experience Questionnaire (UEQ), and a domain-specific seven-item Chatbot Response Quality instrument developed for the Indonesian academic writing context. Between-group differences were analysed using the Mann-Whitney U non-parametric test (α = .05). Findings – The conversational/feature-rich design (Design B) significantly outperformed the formal/minimalist design (Design A) on overall usability (Mean SUS: 88.17 vs. 72.67; p = .002), four of six UEQ dimensions - Attractiveness (p = .018), Perspicuity (p = .041), Stimulation (p = .001), and Novelty (p < .001) - and Indonesian-language chatbot response quality (p = .003). No significant differences were found in UEQ Efficiency (p = .058) or Dependability (p = .237). Research implications – Findings are based on a small single-institution sample (n = 15 per group), limiting generalisability. The domain-specific instrument has not yet undergone full psychometric validation. Results may not transfer uniformly across Indonesia's diverse regional and institutional contexts. Originality – This study is among the first to experimentally compare chatbot interface design variants within an Indonesian-language academic writing context and to develop a domain-specific UX instrument tailored to this setting. The findings provide empirical and actionable design guidelines for developers of Indonesian-language educational chatbots, and establish a replicable research framework for further cross-institutional and longitudinal investigation.
Developing an Integrated Web-Android Augmented Reality Learning Platform for Flat Sailing Science in Maritime Vocational Education Endang Lestari; Masrupah; Wardimansyah Ridwan; Muhammad Hidayat L
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.v4i1.846

Abstract

Purpose – This study aimed to develop and preliminarily validate an integrated web-Android-Augmented Reality (AR) learning media prototype for the Flat Sailing Science course in maritime vocational education. Methods –This study used Research and Development with the ADDIE model. Data were collected through needs analysis, observation, lecturer interviews, black-box functionality testing, and expert validation questionnaires using a five-point Likert scale. Material validation involved four senior lecturers, while preliminary media validation involved one multimedia expert. No cadet usability testing, user-acceptance testing, classroom implementation, or learning-outcome evaluation was conducted in this development cycle; therefore, the study is framed as prototype development, expert validation, and functional readiness testing only. Findings –The product generated three connected components: an AR-enhanced module, a web-based MARITIM IPD platform, and an Android application. Material validation produced an overall normalized descriptive score of 86.67%, while the one-expert media review produced a preliminary score of 85.71%. Black-box testing indicated that the main functions operated according to expected outputs in the final technical check. Research Implications –The product is suitable for expert-informed limited technical piloting, but the evidence remains preliminary. The current findings support descriptive content validity and functional readiness only; they do not demonstrate cadet usability, user acceptance, practicality, classroom implementation success, or learning effectiveness. Originality – This study presents a context-specific prototype that integrates AR visualization, web-based course management, and Android access for Flat Sailing Science in maritime vocational education. The originality claim is limited to this integrated maritime vocational configuration, not to AR learning media in general.
Implementation of a German-Language Voice User Interface as a Pronunciation Practice Medium for Students of German Language Education in Makassar Alamsyah; Syarifah Fatimah; Muftihaturrahmah Burhamzah; Sabrina Saiidi
Journal of Vocational, Informatics and Computer Education Vol 3, No 2 (2025): December 2025
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v3i2.847

Abstract

Purpose – Pronunciation acquisition remains a major challenge for Indonesian learners of German because several German phonemes are absent from the Indonesian phonological system. This study investigated the effectiveness of a German-language Voice User Interface (VUI) as a pronunciation practice medium for undergraduate students in the German Language Education programme at Universitas Negeri Makassar, Indonesia, focusing on five challenging German phonemes: /r/, /ü/, /ö/, /ch/, and /ä:/. Methods – A one-group pretest-posttest quasi-experimental design was employed with 36 undergraduate students. The VUI-based pronunciation intervention was conducted over eight weeks. Data were collected using the Pronunciation Accuracy Rating Scale (PARS), Speech Intelligibility Scores (SIS) assessed by two native-speaker judges (ICC = 0.89), a Pronunciation Confidence Questionnaire (PCQ), and a Technology Acceptance Questionnaire (TAQ). Data were analysed using the Wilcoxon Signed-Rank test (α = .05). Findings – Pronunciation performance improved significantly following the intervention. The overall mean PARS score increased from 50.5 to 72.0, with an N-Gain of 43.4% (Z = −5.241, p < .001, r = 0.87). SIS scores improved from 51.8 to 72.3 (p < .001, r = 0.84). All five PCQ dimensions showed descriptive gains, and the overall PCQ score improved significantly (p < .001, r = 0.86), with the overall confidence mean increasing from 2.64 to 4.05. Technology acceptance was high (TAQ mean = 4.23), and peer recommendation intention received the highest rating (M = 4.44). Among the target phonemes, /r/ and /ä:/ showed the highest N-Gains (45.0% and 44.9%), while /ö/ remained the most challenging (41.1%). The /ch/ phoneme had the lowest pre-test score and the largest absolute gain. Research Implications and Originality – Findings should be interpreted in light of the study’s single-group design, limited sample, short intervention period, and absence of delayed post-testing. This study is the first to evaluate a German-language VUI for pronunciation practice in a South Sulawesi higher education context and contributes an adapted PARS instrument together with evidence-based recommendations for German pronunciation pedagogy.
Machine Learning Classification of Teacher Professional Development Outcomes in North Sulawesi Stralen Pratasik; Arje Cerullo Djamen; Made Krisnanda; Daniel Riano Kaparang
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.v4i2.870

Abstract

Purpose – This study aims to develop and evaluate a machine learning-based classification framework for predicting teacher professional development outcomes in North Sulawesi and to compare the predictive performance of several supervised learning algorithms Methods – A quantitative cross-sectional predictive analytics design was employed involving 520 teachers from primary, lower secondary, and upper secondary schools. Data were collected through validated questionnaires and training evaluation instruments measuring demographic, motivational, institutional, and instructional variables grounded in the Professional Learning Community (PLC) and Technological Pedagogical Content Knowledge (TPACK) frameworks. Five machine learning algorithms, namely Support Vector Machine (SVM), Random Forest (RF), k-Nearest Neighbors (kNN), Naïve Bayes (NB), and Decision Tree (DT), were implemented and evaluated using 20-fold stratified crossFindings – The results revealed that SVM achieved the best performance with an AUC of 93.6%, accuracy of 86.9%, F1-score of 86.9%, and MCC of 73.5%, outperforming RF, NB, DT, and kNN. The findings indicate that teacher development outcomes are influenced by complex interactions among motivational, organizational, and technological factors. Institutional support, collaborative school culture, and technological readiness emerged as critical determinants of successful professional development. Research implications – The cross-sectional design and reliance on questionnaire-based measures limit causal interpretation and generalizability beyond the study context. Originality –This study extends educational data mining research beyond student-centered analytics by integrating PLC and TPACK perspectives into a machine learning framework for teacher professional development evaluation in a developing-country context, providing evidence-based insights for educational policy and intervention planning.

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