Journal of Informatics and Vocational Education
The Journal of Informatics and Vocational Education (JOIVE) is committed to advancing the understanding of applied computer science education, with a particular focus on the integration of informatics in vocational training and the development of innovative teaching and learning methodologies. Pertinent but not limited to the teaching and learning of informatics, including curriculum design, instructional methods, and the use of technology to enhance the educational experience.Vocational Education,Innovative Educational Practices, Educational Technology Development, Impact of Informatics on Society , and Case Studies and Best Practices. JOIVE scope cover all aspect of Informatics Theory, Application, and Vocational Education, including(but not limited): Informatics Theory, Information System, Mobile and Wireless Communication Computer Networks. Distributed System, Cloud Computing, IoT Data Mining, Artificial intelligence, Machine Learning, and Education Learning Technology E-Learning Educational Technology Vocational Education Emerging technologies in education
Articles
51 Documents
<![CDATA[Analysis of Android Applications on Google Play Store as a Learning Media for Java Programming Language ]]>
<![CDATA[Bara Bintang Pradana]]>;
<![CDATA[Endar Suprih Wihidayat]]>;
<![CDATA[Puspanda Hatta]]>
<![CDATA[ Journal of Informatics and Vocational Education Vol. 8 No. 1 (2025): Journal of Informatics and Vocational Education - March ]]>
Publisher : <![CDATA[Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret ]]>
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DOI: 10.20961/joive.v8i1.3471
<![CDATA[Despite the proliferation of Java programming learning applications on mobile platforms, no systematic quality-based framework has been applied to evaluate their instructional adequacy, leaving educators without reliable evidence for media selection. This study aims to systematically evaluate Java programming learning applications available on the Google Play Store to identify those most suitable for use as instructional media. A descriptive qualitative approach with structured assessment was employed, in which applications were systematically collected using predefined keywords and filtered through a six-stage elimination process prior to evaluation. The remaining 30 applications were assessed using the Learning Object Review Instrument (LORI), which evaluates seven aspects: content quality, learning objective alignment, feedback and adaptation, motivation, presentation design, interaction usability, and accessibility. Each aspect was scored on a scale of 1 to 4, and a final percentage score was calculated for each application. Of the 30 applications assessed, three achieved the highest scores: CodeGym (92), Java by Coding and Programming (90), and Java X (89), all of which demonstrated strong performance across content quality and usability dimensions. Notably, Google Play Store user ratings were found to be inversely proportional to LORI-based instructional quality scores, suggesting that popularity metrics do not reflect pedagogical value. These findings indicate that a structured, criteria-based evaluation framework is essential for educators selecting Java learning applications, and that Play Store ratings alone are insufficient as a proxy for instructional quality. Future studies are recommended to validate these findings through user testing with actual learners across multiple educational contexts.]]>
<![CDATA[Developing a Bilingual Digital Story to Promote Honesty and Environmental Awareness in Natural Tourism Settings ]]>
<![CDATA[Mariana Ulfah Hoesny]]>
<![CDATA[ Journal of Informatics and Vocational Education Vol. 9 No. 2 (2026): Journal of Informatics and Vocational Education - July ]]>
Publisher : <![CDATA[Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret ]]>
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DOI: 10.20961/joive.v9i2.3472
<![CDATA[Improving reading skills in junior high school students is a challenge due to low motivation and a lack of engaging materials. This design and development research (DDR) project aimed to address this by developing a digital bilingual storybook for junior high school students. The storybook features illustrations, moral values, and settings based on local nature tourism. The study utilized the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) development model to guide the creation process. Data were collected through teacher interviews, students' questionnaires, expert validation, and product testing. The findings indicated that the developed storybook is highly feasible and received positive feedback from both students and teachers. This storybook not only helps students comprehend bilingual texts but also boosts their motivation and builds character through a connection to their local culture. The result suggests that this material is a valuable tool for enhancing reading skills and instilling positive values in students.]]>
<![CDATA[The Effectiveness of Fast- vs. Slow-Tempo Music on Students’ Cognitive Performance: A Within-Subject Experimental Design ]]>
<![CDATA[Muhammad Rafly Juliawan Fernandes]]>;
<![CDATA[Rizki Hikmawan]]>;
<![CDATA[Rhezwan Dhaifullah Romdhoni]]>
<![CDATA[ Journal of Informatics and Vocational Education Vol. 9 No. 2 (2026): Journal of Informatics and Vocational Education - July ]]>
Publisher : <![CDATA[Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret ]]>
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DOI: 10.20961/joive.v9i2.3478
<![CDATA[This study examined the effects of music tempo on students’ cognitive performance under three conditions: fast-tempo, slow-tempo, and no music. Despite widespread use of music during studying, it remains empirically unclear whether and how music tempo differentially affects cognitive performance among junior high school students in Indonesia. A quantitative approach with a within-subject repeated measures experimental design was employed, involving 34 ninth-grade students from a junior high school in Indonesia. Each participant completed mathematical problem-solving tasks under three controlled conditions: fast-tempo instrumental music (120–190 BPM), slow-tempo instrumental music (60–80 BPM), and silence. Cognitive performance was measured using accuracy scores, and subjective cognitive load was assessed through the NASA-TLX. Data were analyzed using Repeated Measures ANOVA and validated with the Friedman test due to partial violations of normality assumptions. The results indicated that the fast-tempo condition produced the highest mean accuracy, followed by no music and slow-tempo music. However, the differences were not statistically significant, although a moderate effect size suggested practical relevance. Pairwise comparisons revealed a consistent trend favoring fast-tempo music over slow-tempo and no-music conditions. Notably, NASA-TLX scores indicated that the fast-tempo condition produced significantly lower perceived cognitive load (M = 50.07) compared to slow-tempo (M = 61.59), χ²(2) = 13.41, p = .001, suggesting that fast-tempo music reduced subjective mental effort even when accuracy gains were not statistically significant. These findings support the theoretical perspectives of Cognitive Load Theory and arousal-mood theory, indicating that optimal levels of auditory stimulation may enhance cognitive processing efficiency. The results highlight the practical relevance of fast-tempo music in academic settings and underscore the need for further research with larger samples and physiological measures.]]>
<![CDATA[The Influence of Game-Based Learning Assisted by Wordwall on Informatics Learning Outcomes ]]>
<![CDATA[Raihan Bima Agwicahya]]>;
<![CDATA[Basori basori]]>;
<![CDATA[Agus Efendi]]>
<![CDATA[ Journal of Informatics and Vocational Education Vol. 8 No. 1 (2025): Journal of Informatics and Vocational Education - March ]]>
Publisher : <![CDATA[Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret ]]>
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DOI: 10.20961/joive.v8i1.3479
<![CDATA[The research was conducted with the aim of knowing the difference in the effect of the application of game-based learning assisted by Wordwall on the learning outcomes of the informatics class VII SMP Negeri 3 Colomadu. The design of this research is a quasi-experiment. The population used was all seventh-grade students of SMP Negeri 3 Colomadu. The sampling technique used was cluster random sampling, so that the samples used were 32 students from class VII A as the experimental class group and 32 students from class VII B as the control class group. The technique used is by giving tests which include a pretest and a posttest. Prerequisite test by doing the normality test with the Kolmogorov-Smirnov and the homogeneity test with Levene. Data analysis is by independent sample t-test and paired sample t-test with a significant value limit of 0.05 and N-Gain Score, with the help of the SPSS 25 application program. The results obtained show that there is an influence on the application of game- based learning aided by Wordwall on the learning outcomes of the informatics class VII SMP Negeri 3 Colomadu. It can be seen from the calculation of the independent sample t-test, which shows a significance value of 0.036 <0.05, and the paired sample t-test results show a value of 0.000 <0.05. These results show that the use of game-based learning assisted by Wordwall has an effect on learning outcomes. The results on the N-Gain Score also show that the score obtained by the experimental group is higher than the control group, namely 0.4212 > 0.1630. From these results, the experimental group obtained a score that is moderate. These findings suggest that digitally gamified review platforms can serve as effective pedagogical supplements in technology-integrated classrooms, warranting further investigation across diverse subject areas and school contexts.]]>
<![CDATA[Agile-Driven Digital Transformation in Traditional Educational Institutions: Integrating Scrum, Automated Testing, and TAM for Student Registration Systems ]]>
<![CDATA[Anis Nur Choiriyah]]>;
<![CDATA[Nurcahya Pradana Taufik Prakisya]]>;
<![CDATA[Rosihan Ari Yuana]]>
<![CDATA[ Journal of Informatics and Vocational Education Vol. 8 No. 2 (2025): Journal of Informatics and Vocational Education - July ]]>
Publisher : <![CDATA[Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret ]]>
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DOI: 10.20961/joive.v8i2.3482
<![CDATA[Agile methodologies' integration with automated testing and user acceptance evaluation within traditional Islamic boarding school (pesantren) contexts remains understudied. This study develops 'SIAP AMWIN', a web-based student registration system integrating Scrum, Katalon Studio automated testing, and TAM. R&D design was employed across five Scrum cycles (Aug 2023–Feb 2024). A validated 16-item TAM questionnaire (4 Usefulness + 12 Ease of Use items, expert-validated by 2 validators) was administered to 25 new students following system use. Blackbox testing was conducted via Katalon Studio. The system achieved Usefulness 13.96 and Ease of Use 41.44 (overall 86.56%, Very Good), a significant improvement over the prior system score of 12.1 (Not Good). Scrum-driven, actor-centered development effectively enables digital transformation in resource-constrained traditional institutions, providing a replicable blueprint for similar pesantren contexts.]]>
<![CDATA[Machine Learning-Based Early Warning for Student Dropout: Evidence from LMS Behavioral Engagement Patterns in Online Higher Education ]]>
<![CDATA[Rhezwan Dhaifullah Romdhoni]]>;
<![CDATA[Nuur Wachid Abdul Majid]]>;
<![CDATA[Anggita Fitri Permatasari]]>
<![CDATA[ Journal of Informatics and Vocational Education Vol. 9 No. 2 (2026): Journal of Informatics and Vocational Education - July ]]>
Publisher : <![CDATA[Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret ]]>
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DOI: 10.20961/joive.v9i2.3508
<![CDATA[Student dropout in online higher education remains critically high, far exceeding face-to-face rates, yet declining behavioral activity in Learning Management Systems (LMS) offers key signals for early intervention. To identify robust predictors and model suitability for Early Warning Systems (EWS), this study presents a comparative analysis of machine learning for dropout prediction using clickstream data from the Open University Learning Analytics Dataset (OULAD), covering 32,593 students across seven undergraduate modules. Three supervised algorithms with Logistic Regression, Random Forest, and Support Vector Machine (SVM), were trained on 13 engineered features combining behavioral and demographic attributes from the Virtual Learning Environment (VLE), with Recall prioritized to minimize missed at-risk students. Results demonstrate that all models achieved strong discriminatory performance with AUC-ROC > 0.93; specifically, SVM provided the highest EWS fit with recall of 0.903, missing only 196 of 2,031 withdrawals (9.7%), while Random Forest attained the best overall accuracy (0.866) and AUC-ROC (0.940). Feature importance analysis further revealed that VLE behavior accounted for 85.0% of predictive power, with Activity Span emerging as the dominant predictor at 41.3%. Cross-module validation confirmed temporal engagement consistency as a robust, generalizable dropout signal. Therefore, these findings provide practical guidance for implementing data-driven EWS in online learning by prioritizing behavioral span metrics over static demographics]]>
<![CDATA[Development of Interactive E-Modules Based on Blender 3D Visualization: Analysis of Extraneous Cognitive Load and Its Effectiveness on Learning Outcome ]]>
Ashiddiqi, Mujahidin Abdillah; Hikmawan, Rizki; Romdhoni, Rhezwan Dhaifullah
<![CDATA[ Journal of Informatics and Vocational Education Vol. 9 No. 2 (2026): Journal of Informatics and Vocational Education - July ]]>
Publisher : <![CDATA[Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret ]]>
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DOI: 10.20961/joive.v9i2.3519
<![CDATA[The growing demand for technology-based learning media has encouraged the development of interactive e-modules with three-dimensional visualization. However, poorly designed 3D media may increase extraneous cognitive load (ECL) and hinder students’ understanding. This study offers novelty by developing a 3D Blender-based interactive e-module designed with cognitive load management principles, particularly to minimize ECL while improving learning outcomes. The study aimed to develop the e-module and evaluate its impact on students’ cognitive load and achievement. This research used the Research and Development (R&D) method with the ADDIE model. The implementation involved 48 students at the University of Education Indonesia selected through purposive sampling using a one-group pretest-posttest design. Cognitive load was measured using a nine-item psychological scale questionnaire covering ICL, ECL, and GCL, while learning outcomes were assessed using a 15-item multiple-choice test. Data were analyzed descriptively and inferentially using the Shapiro-Wilk normality test and the Wilcoxon Signed Rank Test. The results showed that students’ ECL was low (x̄ = 2.09), indicating that the e-module did not overload working memory. Learning outcomes increased significantly from 34.67% to 84.67% (p = 0.000002). These findings indicate that the proposed e-module effectively supports conceptual understanding while reducing unnecessary cognitive load.]]>
<![CDATA[Immersive TOEFL Preparation in the Metaverse: Usability and Navigability of a Roblox-Based Game Developed via GDLC ]]>
<![CDATA[Rahmawati Salsabila]]>;
<![CDATA[Rizki Hikmawan]]>;
<![CDATA[Rhezwan Dhaifullah Romdhoni]]>
<![CDATA[ Journal of Informatics and Vocational Education Vol. 9 No. 2 (2026): Journal of Informatics and Vocational Education - July ]]>
Publisher : <![CDATA[Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret ]]>
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DOI: 10.20961/joive.v9i2.3520
<![CDATA[Despite the growing adoption of game-based learning in language education, three-dimensional metaverse platforms for TOEFL preparation remain critically underexplored, leaving learners reliant on drill-based 2D media that lack immersion and sustained engagement. This study addresses that gap by developing a Roblox-based TOEFL learning game using the Game Development Life Cycle (GDLC) and evaluating user understanding of its game flow through graduated formative evaluation. An R&D design was employed, implementing six GDLC stages alongside Tessmer's formative evaluation: one-on-one (n=3), small group (n=5), and field testing (n=40). Data were gathered via observation, interview, and Likert-scale questionnaires, and analyzed descriptively. The game was realized as an area-based environment with three thematic zones and a multi-level navigation system. Evaluations showed progressive quality improvement: one-on-one (M=3.25), small group (M=4.00), and field testing (M=3.84, 96.3% positive response), indicating satisfactory usability and navigability. However, awareness of the Challenge Room and return-route comprehension remain areas requiring refinement. Theoretically, this study demonstrates that GDLC paired with formative evaluation provides a structured and iterative framework for validating metaverse-based educational games. Practically, the findings offer actionable design principles for educators and developers building immersive, game-based language learning environments within social 3D platforms]]>
<![CDATA[Learning Innovation Strategies and Their Role in Promoting Student Active Participation in Informatics Education: A Qualitative Inquiry ]]>
Majid, Aysie Safar Abdul; Budianto, Aris; Basuki, Basuki
<![CDATA[ Journal of Informatics and Vocational Education Vol. 8 No. 2 (2025): Journal of Informatics and Vocational Education - July ]]>
Publisher : <![CDATA[Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret ]]>
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DOI: 10.20961/joive.v8i2.3556
<![CDATA[Active student participation is a recognized indicator of effective learning, yet passive engagement remains prevalent in Indonesian secondary classrooms, particularly in technology-intensive subjects such as Informatics. This qualitative descriptive study investigated how learning innovations implemented by an Informatics teacher influenced student active participation at a senior high school in Sukoharjo, Central Java, Indonesia. Using purposive sampling, eight participants were selected, comprising seven Grade XI students (six female, one male) and one experienced Informatics teacher. Data was collected through a direct semi-structured teacher interview of approximately 30 minutes, structured written responses from students comprising 13 open-ended questions, and classroom observation. Data was analyzed using thematic analysis. Three key themes emerged from the findings. First, practical and laboratory-based activities were the primary drivers of student engagement, with six of seven students reporting higher motivation during hands-on sessions. Second, teacher instructional methods, particularly interactive, discussion-based, and project-oriented approaches, directly influenced students' willingness to ask questions and contribute to group work. Third, individual interest in Informatics varied considerably, with one student expressing low motivation due to language barriers in English-language materials, highlighting the need for differentiated instruction. These findings suggest that contextually relevant, practice-centered learning innovations are essential for fostering active participation in Informatics education at the senior high school level in Indonesia.]]>
<![CDATA[Early Fire Detection Using IoT and Deep Learning ]]>
<![CDATA[Syandhu Dea Fermanda]]>;
<![CDATA[Zikri Wahyuzi]]>;
<![CDATA[Arvi Pramudyantoro]]>
<![CDATA[ Journal of Informatics and Vocational Education Vol. 9 No. 3 (2026): November 2026 ]]>
Publisher : <![CDATA[Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret ]]>
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DOI: 10.20961/joive.v9i3.3515
<![CDATA[Fire incidents in strategic facilities such as weapon storage rooms can cause severe damage, threaten personnel safety, and disrupt operational readiness. Conventional fire detection systems generally rely on smoke or temperature sensors, which often respond only after hazardous conditions reach a certain threshold. Therefore, this study proposes an early fire prevention system based on Internet of Things (IoT) and deep learning using CCTV cameras. The system was developed using the System Development Life Cycle (SDLC) with the Waterfall model. The object detection model employed YOLOv8 and was trained on a laptop before being deployed to a Raspberry Pi 5 as the real-time processing unit. The implemented hardware consisted of a Raspberry Pi 5, a Logitech webcam, monitor, keyboard, and mouse. Testing was conducted in a room measuring 6 m × 4 m × 3.5 m. The developed system successfully detected four object classes, namely fire, smoke, cigarette, and person. The implemented logic mechanism classified fire detection as a fire incident, while simultaneous cigarette and smoke detection was categorised as smoking activity with potential fire risk. In addition, the system successfully sent automatic warning notifications through Telegram, enabling faster response without continuous manual monitoring. The results indicate that combining YOLOv8, Raspberry Pi 5, and IoT communication can provide an effective, practical, and low-cost intelligent fire prevention solution for indoor strategic facilities.]]>
