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Journal of Informatics and Vocational Education
Published by Universitas Sebelas Maret
ISSN : -     EISSN : 27467813     DOI : 10.20961/joive
Core Subject : Science, Education, Social,
Computer Science & IT Education Social Sciences
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
Arjuna Subject : Ilmu Sosial - Pendidikan
Articles 51 Documents
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Enriched Virtual Blended Learning Model Assisted by Digital Comics: Its Effect on Student Learning Motivation Ryan Brilian Fatsena; Basori; Agus Efendi
Journal of Informatics and Vocational Education Vol. 7 No. 3 (2024): Journal of Informatics and Vocational Education - November
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v7i3.2410

Abstract

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.
Security Analysis of Web-based Information Systems Through Vulnerability Assessment  Using the Framework of OWASP Web Security Testing Guide and Common Vulnerability Scoring System Muhammad Rifqy Abdallah; Puspanda Hatta; Cucuk Wawan Budiyanto
Journal of Informatics and Vocational Education Vol. 7 No. 3 (2024): Journal of Informatics and Vocational Education - November
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v7i3.2411

Abstract

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.
Python-Based Mapping of Productive Technical Teachers Using Google Colab in Tuban’s Vocational High Schools Muhamad Nur Azmi Wahyudi; Alhaura Nabighatul Ula; Yuyun Estriyanto; Budi Tri Cahyono
Journal of Informatics and Vocational Education Vol. 8 No. 3 (2025): Journal of Informatics and Vocational Education - November
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v8i3.2516

Abstract

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.
Integrating Technology-Based Tools in the Digital Marketing Course to Enhance Vocational Students’ Engagement and Competence in Promoting Local Culinary Destinations Slamet Kurniawan Fahrurozi; Muhammad Hassan Massaty
Journal of Informatics and Vocational Education Vol. 8 No. 3 (2025): Journal of Informatics and Vocational Education - November
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v8i3.2682

Abstract

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.
Mapping the Research Landscape of Green Skills in Vocational Education: A Systematic Literature and Network Analysis Haen Muhaemanurrohmah; Isma Widiaty
Journal of Informatics and Vocational Education Vol. 9 No. 1 (2026): Journal of Informatics and Vocational Education - March
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v9i1.2972

Abstract

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.
AI Based Digital Book Indexing System Using YAKE and WORD2VEC Methods Mohammad Alfarizi Abdullah; Ulla Delfana Rosiani; Vit Zuraida; Arhan Windu Rizki Putra Budianto; Rizki Putri Ramadhani
Journal of Informatics and Vocational Education Vol. 9 No. 1 (2026): Journal of Informatics and Vocational Education - March
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v9i1.3026

Abstract

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.
Automatic Indexing of Digital Books using RAKE and Word2Vec Arhan Windu Rizki Putra Budianto; Ulla Delfana Rosiani; Vit Zuraida; Rizki Putri Ramadhani; Mohammad Alfarizi Abdullah
Journal of Informatics and Vocational Education Vol. 9 No. 1 (2026): Journal of Informatics and Vocational Education - March
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v9i1.3050

Abstract

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.
Pemberdayaan Keterampilan Abad 21 melalui Pendekatan Konstruktivis dalam Pembelajaran Informatika di Sekolah Menengah Atas (SMA) Ardhian Akbar Ahmadi; Cucuk Wawan Budiyanto; M. Khasan Tiarani
Journal of Informatics and Vocational Education Vol. 8 No. 1 (2025): Journal of Informatics and Vocational Education - March
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v8i1.3174

Abstract

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.
The Influence of Self-Efficacy and Learning Independence on the Job Readiness of Informatics Education Graduates Rizka Rizkianna; Agus Efendi; Dwi Maryono
Journal of Informatics and Vocational Education Vol. 8 No. 2 (2025): Journal of Informatics and Vocational Education - July
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v8i2.3181

Abstract

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.
Classification of Batik Cual Bangka Belitung Based on Deep Learning: YOLOv11 Approach Andika Saputra; Zikri Wahyuzi; Yudistira Bagus Pratama
Journal of Informatics and Vocational Education Vol. 9 No. 1 (2026): Journal of Informatics and Vocational Education - March
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v9i1.3208

Abstract

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.

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