Journal of Informatics and Vocational Education
Journal Title Journal of Informatics and Vocational Education Initials JOIVE Frequency 3 (Three) Issues Annually: March, July, and November E-ISSN 2746-7813 Chief Editor Dr. Aris Budianto, ST, M.Eng. DOI Prefix 10.20961/joive Publisher Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret Accreditation Sinta 3 Accredited JOIVE is a peer-reviewed journal providing a forum for presenting the latest original research results and developments in the fields of informatics and applied computer science education. The journal promotes discussion among researchers, students, and practitioners in informatics and practical educators both in Indonesia and beyond where a distinctive methodology of teaching and learning informatics has been developed and is of great interest. Important Note: Starting from Volume 7, Issue 2 (2024), JOIVE has upgraded its system from OJS2 to OJS3 (this website). Please note that old accounts on the OJS 2 system are different and cannot be used in the new OJS 3 system. For submission purposes, authors are required to create a new account on the new website. The archives of previous publications using OJS2 (up to Volume 7, Issue 1, 2024) can be accessed through the old website: https://jurnal.uns.ac.id/joive/. INDEXED :
Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret
Development of Interactive E-Modules Based on Blender 3D Visualization: Analysis of Extraneous Cognitive Load and Its Effectiveness on Learning Outcome
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.
Copyright (c) 2026 Journal of Informatics and Vocational Education https://creativecommons.org/licenses/by-sa/4.0/
Learning Innovation Strategies and Their Role in Promoting Student Active Participation in Informatics Education: A Qualitative Inquiry
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.
Copyright (c) 2025 Journal of Informatics and Vocational Education https://creativecommons.org/licenses/by-sa/4.0/
Immersive TOEFL Preparation in the Metaverse: Usability and Navigability of a Roblox-Based Game Developed via GDLC
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
Machine Learning-Based Early Warning for Student Dropout: Evidence from LMS Behavioral Engagement Patterns in Online Higher Education
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
Agile-Driven Digital Transformation in Traditional Educational Institutions: Integrating Scrum, Automated Testing, and TAM for Student Registration Systems
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.
The Influence of Game-Based Learning Assisted by Wordwall on Informatics Learning Outcomes
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.
The Effectiveness of Fast- vs. Slow-Tempo Music on Students’ Cognitive Performance: A Within-Subject Experimental Design
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.
Developing a Bilingual Digital Story to Promote Honesty and Environmental Awareness in Natural Tourism Settings
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.
Analysis of Android Applications on Google Play Store as a Learning Media for Java Programming Language
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.
Development of Interactive Learning Media for Vocational High Schools in Basic Computer Network and Telecommunication Engineering Subjects
The development of technology in the Industry 4.0 era has brought significant changes in many aspects of life, including our education. In the formal education system, teachers play a crucial role in creating an engaging and effective learning environment. This research aims to develop an interactive learning media called Comneter (Computer Network Learning) as a learning media to help students with their understanding of basic computer networks and telecommunication in vocational high schools. Comneter was developed using Unity software, a cross-platform game engine that enables us to create apps for both mobile and desktop platforms. The method used for this research is the Research and Development (R&D) method, with ADDIE (Dick et al., 1996) as the model of this development. This model consists of 5 main phases, including analysis, design, development, implementation, and evaluation. The results from this research show that Comneter received a feasibility assessment from a material expert, a media expert, students, and a teacher (as a respondent), with an average score of 3.96, categorizing Comneter as ‘Good’ or feasible. Therefore, it can be concluded that, based on this research, using computers can help enhance students’ comprehension in basic computer network and telecommunications engineering subjects, and has the potential to be used in vocational high schools to create a more effective and engaging learning experience
An Experimental Study on the Comparison of Learning Outcomes in VLAN Configuration Using Graphical Network Simulator 3 and Cisco Packet Tracer
Selecting an appropriate network simulator for advanced VLAN instruction in higher education remains an unresolved pedagogical challenge, as empirical comparisons of GNS3 and Cisco Packet Tracer at university level are scarce. This study aimed to examine (1) whether a significant difference in VLAN configuration learning outcomes exists between students using GNS3 and those using Cisco Packet Tracer, and (2) the relative effectiveness of each simulator for students of the Informatics and Computer Engineering Education Program (PTIK) at Universitas Sebelas Maret. A quasi-experimental pre-test–post-test design was employed with two intact classes (N = 30) from the 2023 cohort, randomly assigned to the GNS3 condition (n = 15) and the Cisco Packet Tracer condition (n = 15). Learning outcomes were measured using ten validated essay items (α = 0.673) and analysed via an independent-samples t-test and normalised gain (N-gain) index. Results revealed that GNS3 users outperformed Packet Tracer users on the post-test (mean 79.33 vs. 72.80), with a statistically significant difference (t (28) = 2.224, p = 0.034). N-gain analysis further showed that the GNS3 group achieved moderate learning effectiveness (g = 0.452), compared to the low category recorded for the Cisco Packet Tracer group (g = 0.277). These findings suggest that GNS3’s authentic Cisco IOS emulation fosters deeper cognitive engagement with advanced VLAN tasks—including inter-VLAN routing and native CLI syntax—than the abstracted environment of Packet Tracer. GNS3 is therefore recommended as the primary simulator for advanced networking courses in higher education, while Packet Tracer remains appropriate for introductory-level instruction. Future research should replicate this design with larger, multi-institutional samples to strengthen external validity.
Enhancing Learning Outcomes in Vocational Animation Education: A Quasi-Experimental Study of Kahoot-Assisted Game-Based Learning in Indonesia
Student disengagement during theory-based instruction in vocational high schools remains a critical pedagogical challenge. Game-based learning (GBL) has emerged as an innovative approach to improve student engagement and achievement, particularly in vocational education. This study aimed to examine the difference in learning outcomes and the effectiveness of the Kahoot-assisted GBL model compared to conventional learning in the 2D Animation subject. A quasi-experimental pretest-posttest control group design was employed. Sixty-one grade XI Multimedia students at a vocational high school in Surakarta were selected through cluster random sampling (experimental n=30, control n=31). Data were collected via validated achievement tests and analyzed using an independent sample t-test and normalized gain index. Results showed a significant difference in learning outcomes (t=5.548, p=0.000<0.05). The normalized gain score of the experimental class (g=0.52, medium category) was significantly higher than the control class (g=0.20, low category). Kahoot-assisted GBL is more effective than conventional learning in improving student learning outcomes in 2D Animation. These findings offer evidence-based guidance for vocational educators seeking to enhance theory-based learning through gamified digital tools. This study contributes to the limited body of evidence on gamified learning in vocational multimedia education within the developing country context.
Learning Barriers in Web Programming Subjects Among Vocational Software Engineering Students: A Qualitative Case Study
This study examines the learning difficulties experienced by vocational high school (SMK) students in the Computer and Network Engineering (TKJ) program in learning web programming. A qualitative case study approach was employed, involving semi-structured interviews, observations, and documentation with 21 students from SMK Negeri 2 Buduran. Data were analyzed using thematic analysis supported by descriptive questionnaire results. The findings show that all students perceived web programming as challenging, with 71% rating it as very difficult and 29% as moderately difficult, while none considered it easy. In terms of learning enjoyment, 76% of students reported a neutral level of enjoyment, indicating limited intrinsic motivation. The analysis revealed several dominant learning barriers, including difficulties with programming syntax and logic, challenges in using development tools such as VSCode and terminal environments, limited access to clear learning resources, and insufficient instructional guidance. Emotional factors, such as frustration and stress caused by repeated errors, further hindered the learning process. Students also identified programming, networking (e.g., TCP/IP and server administration), and microcontroller-related subjects as the most difficult areas within the curriculum. These findings indicate that students’ learning difficulties in web programming are not only technical but also instructional and affective in nature. Therefore, this study emphasizes the need for more interactive, supportive, and student-centered learning strategies. The adoption of project-based learning, enhanced digital learning resources, and guided mentorship is recommended to improve students’ competencies, motivation, and confidence in web programming. The results provide valuable insights for educators, curriculum developers, and policymakers in strengthening vocational education to better meet industry demands.
Instructors’ Acceptance of Roblox Studio for Informatics Education: An Extended TAM with Perceived Risk
The increasing integration of immersive digital platforms in education has created new opportunities for game-based learning; however, tutors’ acceptance of game development platforms remains insufficiently explored in empirical research. This study investigates the factors influencing tutors’ intention to adopt Roblox Studio as a learning platform in informatics education by applying an Extended Technology Acceptance Model (TAM) integrated with perceived risk. Data were collected from 125 informatics tutors in Indonesia using a structured questionnaire and analyzed using Covariance-Based Structural Equation Modeling (CB-SEM) with a Robust Maximum Likelihood estimator. The results indicate that the proposed model explains 84.3% of the variance in behavioral intention to use Roblox Studio. Perceived Ease of Use significantly influences Perceived Usefulness, while Attitude Toward Using emerges as the strongest predictor of tutors’ adoption intention. Interestingly, Perceived Ease of Use and Perceived Usefulness do not significantly affect tutors’ attitudes, suggesting that pedagogical considerations may play a more dominant role than purely technical factors in technology adoption decisions. Furthermore, perceived risk does not significantly reduce adoption intention, indicating that tutors tend to prioritize the pedagogical benefits of immersive platforms over potential technological concerns. This study contributes to the literature by extending the Technology Acceptance Model within the context of game-development platforms and providing empirical insights into tutor perspectives in game-based learning adoption. The findings offer practical implications for educators and institutions seeking to integrate immersive digital platforms into informatics education.
Enhancing Students’ Motivation in Algorithm Learning through Web-Based Visual Diagramming Tools: An ARCS Model Analysis
Learning algorithms and flowchart design in secondary informatics education often lack engaging instructional strategies that effectively foster students’ learning motivation. However, limited studies have examined how web-based visual diagramming tools influence students’ motivational dimensions in algorithm learning within the ARCS framework. This study provides empirical evidence on how web-based diagramming tools enhance motivational engagement in algorithm learning. A qualitative descriptive design was employed involving 36 tenth-grade students. The findings reveal that visual interaction through draw.io significantly increased students’ attention and engagement, improved contextual relevance of learning tasks, strengthened learners’ confidence in constructing flowcharts independently, and generated positive learning satisfaction. These findings extend the application of the ARCS model within web-based informatics instruction and highlight the potential of digital visual tools to enhance affective learning outcomes. Integrating digital visual media into informatics instruction can serve as an effective strategy to enhance students’ motivation and engagement in computational learning.
Human–GenAI Score Alignment in Rubric-Constrained Essay Assessment: Procedural Convergence Without Pedagogical Equivalence
The increasing availability of Generative Artificial Intelligence (GenAI) systems has raised critical questions regarding their role in educational assessment, particularly in evaluating open-ended student responses that traditionally rely on professional teacher judgment. This study investigates the extent to which GenAI-generated scores align with teacher assessments when both are guided by an explicit and standardized rubric framework. Using a parallel scoring design, written responses from junior secondary school students were independently evaluated by an Informatics teacher and a GenAI system (ChatGPT) based on an identical rubric encompassing progressively increasing cognitive demands from lower-order to higher-order thinking skills. To examine scoring alignment, an Intraclass Correlation Coefficient (ICC) analysis with a two-way mixed-effects model and absolute agreement approach was employed. The results indicate a meaningful level of score alignment between teacher and GenAI assessments, suggesting that GenAI can apply rubric-based evaluative criteria in a procedurally consistent manner. However, qualitative analysis of written feedback reveals substantive differences in pedagogical depth. While GenAI feedback demonstrates high structural consistency and transparent rubric justification, teacher feedback exhibits greater contextual sensitivity, incorporating instructional intent, student misconceptions, and classroom dynamics. These findings suggest that GenAI systems hold potential as assessment support tools capable of enhancing scoring consistency and efficiency in formative assessment contexts. Nevertheless, score alignment should not be interpreted as pedagogical equivalence. The study concludes that GenAI is best positioned as an augmentative decision-support system operating under teacher supervision, rather than as an autonomous assessor. This research contributes empirical evidence to ongoing discussions on Human–AI score alignment and highlights the critical role of rubric design in mediating responsible GenAI integration within educational assessment practices.
Analysis of Social-Emotional Development Through Collaborative Learning of Informatics Subjects for High School Students
This study aims to analyze the implementation of collaborative learning based on crossword puzzles and its relationship to the social-emotional development of class X E5 students. This study uses a qualitative descriptive approach and data collection through observation and documentation during the learning process. This study shows that the implementation of collaborative learning strategies based on crossword puzzles can increase learning interactions actively and optimally. This is seen from the increase in empathy, self-confidence, communication, interactivity, and the ability to work together in groups. This study shows that the integration of collaborative learning with crossword puzzles not only supports the understanding of computer network concepts but also plays a role in the social-emotional development of students. Thus, collaborative learning based on crossword puzzles can be an innovative learning strategy in informatics subjects that is holistically oriented.
Integration of Artificial Intelligence Models into a Flask-Based Web Application for Classification and Generation of Batik Cual Motifs from Bangka Belitung
Artificial Intelligence (AI) has been increasingly adopted to support digital preservation and creative exploration of cultural heritage. However, many existing studies primarily focus on model development, while limited attention is given to the practical integration and deployment of AI models in real-world applications. This study presents the integration of AI models into a web-based application using the Flask framework for Batik Cual motif classification and generation. The proposed system enables users to interact with AI functionalities through a browser-based interface, supporting motif classification from uploaded images and motif generation based on textual input and reference images. The integration is implemented using a RESTful backend architecture, where Flask manages request handling, preprocessing, AI inference workflows, postprocessing, and result visualization. Functional testing results indicate that the system operates according to its intended design, providing structured outputs with acceptable response times. The findings demonstrate that Flask is an effective and practical framework for deploying AI-driven web applications, particularly for prototype-scale systems aimed at supporting digital preservation and dissemination of traditional cultural motifs.
Generation of Batik Cual Bangka Belitung Motif Variations Using Stable Diffusion Models
Batik Cual Bangka Belitung is a visual cultural heritage characterized by repetitive motifs, fine line details, and high ornament complexity, presenting significant challenges for digital exploration without compromising its visual identity. This study aims to generate variations of Batik Cual motifs using a prompt-guided image-to-image (img2img) approach based on the Stable Diffusion model with a single-reference image. Furthermore, the research analyzes the influence of the strength parameter on the delicate balance between structural similarity and generative visual variation. The dataset consists of 13 independently collected Batik Cual motifs, pre-processed through RGB conversion and standardized to a resolution of 512×512 pixels. Controlled experiments were conducted using varied strength values of 0.4, 0.6, and 0.8, while maintaining other parameters constant. Quantitative evaluation utilized the Structural Similarity Index Measure (SSIM) to assess structural integrity and CLIP similarity to measure semantic alignment between the prompt and output image. The results indicate that increasing strength consistently decreases SSIM values, signifying greater structural deviation from the reference image, whereas CLIP similarity remains relatively stable across configurations. Quantitatively, a strength of 0.4 offers the optimal combination of structural similarity and semantic suitability. However, qualitative assessments reveal that for certain motifs, a strength of 0.6 produces a more balanced variation between pattern innovation and motif character preservation. These findings confirm a measurable trade-off between identity preservation and generative exploration, demonstrating the potential of Stable Diffusion as a controlled method for developing Batik Cual digital assets.
Classification of Batik Cual Bangka Belitung Based on Deep Learning: YOLOv11 Approach
The rapid growth of artificial intelligence, particularly deep learning, has enabled significant advancements in computer vision and automated image recognition. However, the application of these technologies to traditional cultural artifacts remains limited, especially within the domain of Indonesian textile heritage. Batik Cual Bangka Belitung, which features intricate ornamentation and visually similar motifs, presents unique classification challenges that conventional Convolutional Neural Network (CNN) models struggle to address effectively. To overcome these limitations, this study introduces an automatic motif classification system using the YOLOv11 architecture, a state-of-the-art object detection model capable of identifying and distinguishing fine-grained visual patterns. The research follows a systematic pipeline consisting of dataset collection, curation, manual motif labeling, image preprocessing, model configuration, training, and testing. A curated dataset of Batik Cual images was augmented and divided into training, validation, and testing subsets to ensure robust evaluation. Experimental results demonstrate strong model performance, achieving a precision of 0.934, recall of 0.808, mAP50 of 0.950, and mAP50–95 of 0.8172. These findings confirm that YOLOv11 can accurately detect motif regions and classify them under varying structural and textural conditions. The study contributes not only a reliable technical framework for recognizing Batik Cual motifs, but also supports digital preservation efforts and future cultural computing applications.
Mapping the Research Landscape of Green Skills in Vocational Education: A Systematic Literature and Network Analysis
Green skills integration in vocational education and training (VET) represents a critical priority for sustainable workforce development, yet systematic understanding of effective implementation approaches remains fragmented. This systematic literature and network analysis (SLNA) integrates dual methodological approaches—bibliometric analysis mapping 314 publications and systematic review synthesizing eleven empirical studies—to comprehensively characterize the research landscape and identify evidence-based strategies for green competency development. The systematic review followed PRISMA 2020 guidelines, searching Scopus database (2014-2025) with two-stage screening yielding eleven studies spanning nine countries. The bibliometric component employed VOSviewer keyword co-occurrence analysis, generating seven thematic clusters with temporal overlay visualization. Systematic findings documented holistic framework superiority over standalone interventions, with comprehensive build-in strategies demonstrating higher effectiveness than retrofitted approaches. Bibliometric networks revealed three-phase field development from foundation (2022-2023) through consolidation (2023-2024) to innovation (2024-2025), with behavioral measurement emerging as newest focus. Dual-source validation confirmed teacher capacity as critical implementation bottleneck. Effective green skills integration requires holistic frameworks, comprehensive build-in strategies, and priority teacher development investment. Future research priorities include longitudinal behavioral studies, climate-specific competency development, and technology integration evaluation.
The Influence of Self-Efficacy and Learning Independence on the Job Readiness of Informatics Education Graduates
The research aims to understand the relationship between self-efficacy and independent student learning readiness among working students. The research methodology used a correlational study. The population that was used in the research was all students in the XII computer engineering program at SMK Muhammadiyah 1 Sukoharjo, covering 143 students. While the research sample of 72 students was obtained by a cluster random sampling method of sampling. Data collection in this research uses three that is scales of self-efficacy, scales of independent learning, and scales of readiness for work students that have been tested for validity and reliability. The result showed that self-efficacy and independent learning have a positive and significant relationship with readiness for work students, whether independent or simultaneous. These findings imply that strengthening self-efficacy and developing independent character are crucial for schools in improving graduates' work readiness for the workplace.
Pemberdayaan Keterampilan Abad 21 melalui Pendekatan Konstruktivis dalam Pembelajaran Informatika di Sekolah Menengah Atas (SMA)
Pendidikan Informatika di era digital menuntut pergeseran dari sekadar penguasaan materi menuju pengembangan berpikir kritis, namun penelitian mengenai implementasi konstruktivisme spesifik pada siswa SMA kelas 10 masih terbatas. Penelitian kualitatif ini bertujuan untuk mengeksplorasi penerapan pendekatan tersebut melalui observasi partisipatif dan wawancara mendalam dengan guru Informatika. Hasil penelitian menunjukkan bahwa strategi eksplorasi mandiri pada materi aplikasi perkantoran secara signifikan meningkatkan keterlibatan siswa dan pemahaman konsep nyata. Studi ini menyimpulkan bahwa efektivitas konstruktivisme dalam Informatika sangat bergantung pada manajemen kelas yang adaptif dan dukungan fasilitas pembelajaran. Temuan ini memberikan implikasi praktis bagi perancangan strategi pengajaran yang fleksibel di sekolah menengah.
Automatic Indexing of Digital Books using RAKE and Word2Vec
Manual indexing of digital books is time-consuming and prone to inconsistency. To address this, this study developed an automatic indexing system using RAKE (Rapid Automatic Keyword Extraction) method and Word2Vec. The system accepts PDF files as input, performs text preprocessing, and extracts key phrases using RAKE. These phrases are subsequently filtered based on semantic relevance to the specified topic using an Indonesian-language Word2Vec model. Users can manually add phrases and select relevant ones to be included in the final index. The resulting index includes phrases, page numbers, and relevance scores, which are inserted as an additional page at the end of the PDF document. Evaluation was conducted by comparing the system-generated index with the author’s manual index using precision, recall, and cosine similarity metrics. The results indicate that although precision and recall were very low, a cosine similarity score of 0.69 suggests a semantic similarity between the system output and the author’s index.
AI Based Digital Book Indexing System Using YAKE and WORD2VEC Methods
Polinema Press, the publishing unit of the State Polytechnic of Malang (Polinema), requires an efficient solution for automatically generating book indexes. The current manual indexing process is time-consuming and inefficient. This research aims to develop an AI-based automatic indexing system utilizing the YAKE (Yet Another Keyword Extractor) and Word2Vec methods to improve the accuracy and efficiency of index generation. The system is designed to process digital books in PDF format through several stages: (1) text preprocessing (text extraction, stopword removal, tokenization), (2) keyword extraction using YAKE based on statistical features such as word frequency and position, (3) final keyword selection by measuring semantic similarity using Word2Vec, and (4) alphabetical index compilation along with page numbers where keywords appear. The indexing results are evaluated by comparing them with manual indexes using cosine similarity to measure the degree of similarity. This research has been tested on 37 digital books and resulted in the best configuration in the combination of YAKE and Word2Vec with phrases of 2-3 words, which obtained cosine similarity values of up to 0.91, precision of up to 0.38, and average processing time of less than 4 seconds per document. These results show that the system is able to produce relevant, fast, and contextual indexes when compared to manual indexes, and is expected to reduce the manual workload at Polinema Press and become a reference for the application of natural language processing (NLP) technology for Indonesian-language documents.
Integrating Technology-Based Tools in the Digital Marketing Course to Enhance Vocational Students’ Engagement and Competence in Promoting Local Culinary Destinations
This study investigated the impact of integrating technology-based tools into a semester-long Digital Marketing course on vocational students’ engagement and competence in promoting local culinary destinations. Conducted as a qualitative case study at a vocational institution in Indonesia, the research involved 28 students who participated in authentic, project-based learning tasks using tools such as AI-assisted video editors, social media analytics, and digital branding platforms. Data were collected through interviews, field observations, and analysis of student project artifacts. The results revealed increased behavioral, emotional, and cognitive engagement, driven by the relevance of the tools, the authenticity of tasks, and the public nature of the projects. Students also demonstrated meaningful competence in digital storytelling, campaign planning, and platform optimization. Furthermore, the study found emerging signs of critical digital literacy and professional identity development, as students reflected on ethical considerations and strategic decisions during content creation. These findings suggest that the thoughtful integration of real-world digital tools can enhance not only skill acquisition but also reflective and identity-forming dimensions of learning in vocational contexts. The study highlights the pedagogical value of designing curriculum-integrated, technology-enhanced instruction that aligns with both industry demands and community engagement.
Python-Based Mapping of Productive Technical Teachers Using Google Colab in Tuban’s Vocational High Schools
The availability of productive subject teachers is a crucial factor in ensuring the quality of vocational education, particularly at the level of Vocational High Schools (SMK). This report presents the results of a mapping study on the adequacy of productive teachers in technical departments at public SMKs in Tuban Regency, under the supervision of the Regional Education Office of Bojonegoro. The study aims to identify the distribution of productive teachers across departments, assess their adequacy based on the ideal minimum requirements, and determine whether there is a shortage or surplus relative to the ideal maximum needs. Data were obtained from official school reports and analyzed using descriptive quantitative methods. The findings show that 96% of the 25 mapped departments have met the minimum required number of productive teachers, while one department still faces a shortage. On the other hand, 36% of the departments have a surplus of teachers, as the number exceeds the ideal maximum threshold. The distribution of teachers also reveals disparities both within schools (between departments) and among different schools. This mapping provides valuable insight for schools and the regional education authority in planning teacher redistribution, recruitment, and dual-skill training. Furthermore, the results underscore the importance of developing a more dynamic and integrated teacher data system to support sustainable human resource planning in vocational education.
Security Analysis of Web-based Information Systems Through Vulnerability Assessment Using the Framework of OWASP Web Security Testing Guide and Common Vulnerability Scoring System
The technology of web-based information systems continues to develop and has been adopted by many organizations, including higher education institutes. However, this technology carries inherent security risks, making regular security analysis essential. This research presents a case study of eight web-based information systems at a higher education institution to assess the security condition of each system individually and its overall characteristics, as well as to construct an advanced strategy for maintaining and optimizing system security. The security analysis was conducted using a mixed-method approach: qualitatively through the OWASP Web Security Testing Guide framework across four categories (Information Gathering, Configuration and Deployment Management Testing, Session Management Testing, and Client-side Testing); and quantitatively through Common Vulnerability Scoring System (CVSS) calculations. All information systems tested were found to be vulnerable, though with varying levels of severity. Vulnerability discovery ratios ranged from a low of 8% (with a 'Low' severity level) to a high of 31% (with severity levels reaching 'Critical'). Overall, systems based on a Content Management System (CMS) were found to be less vulnerable compared to those built on non-CMS frameworks. Based on the discovered vulnerabilities, follow-up recommendations were constructed to serve as a reference for improving and optimizing the systems' security.
Copyright (c) 2025 Journal of Informatics and Vocational Education
Enriched Virtual Blended Learning Model Assisted by Digital Comics: Its Effect on Student Learning Motivation
The Enriched Virtual Blended Learning model, assisted by digital comics, has attracted attention in the world of education for its positive influence on student motivation. This model requires students to study material both before and after class sessions. An experimental research method was used to determine the effect of this learning model on student motivation, as defined by four key indicators: "Feelings of Joy," "Student Involvement," "Interest," and "Student Attention." This experimental study proves that a significant change occurs when using this learning model. The results show a significance value (2-tailed) of 0.000, which is less than the significance level of 0.05. Thus, it is concluded that the application of the Enriched Virtual Blended Learning model assisted by digital comics has a significant influence on student learning motivation. By incorporating various factors that can increase student motivation, this model provides a positive influence on achieving learning objectives.
Increasing Student Interest in Interactive Multimedia Product Creation Subject through Scratch-Based Learning Media
Engaging students is essential in education. If students are interested in a subject, they will study it repeatedly, driven by their intrinsic motivation to achieve a goal. However, one of the schools, SMK N 1 Demak, has experienced problems with students' interest in learning. A teacher stated that during lessons for the "Making Interactive Multimedia Products" subject, students were often unfocused and did not pay attention, which is a characteristic of a lack of interest. This study aims to design learning media using the Scratch application to increase the interest of class XII students in making interactive multimedia products at SMK Negeri 1 Demak. The data collection techniques used were interviews and questionnaires. Data validity was ensured using construct validity techniques, while data analysis was performed using comparative descriptive and critical analysis techniques. The research procedure followed the ADDIE model. At the beginning of the application development, the developer consulted with subject and media experts. The measurement instruments were validated by an educational expert. The analysis of the results used descriptive percentages. The findings showed that the application of Scratch multimedia successfully increased students' interest in making interactive multimedia products in the class XII multimedia program at SMK Negeri 1 Demak.