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M. Miftach Fakhri
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Journal of Vocational, Informatics and Computer Education
Published by PT. Academic Bright Collaboration
ISSN : 29884918     EISSN : 29886325     DOI : https://doi.org/10.66053/voice
Core Subject : Science, Education,
Computer Science & IT Education
1. Informatics and Computing Research addressing the design, development, implementation, and evaluation of computing technologies relevant to educational, professional, and digital learning environments, including but not limited to: Artificial Intelligence and Machine Learning Deep Learning and Neural Networks Data Science, Big Data, and Data Analytics Software Engineering and Software Development Computer Networks and Internet Technologies Cloud Computing and Distributed Computing Systems Internet of Things (IoT) and Smart Systems Human–Computer Interaction (HCI) and User Experience (UX) Intelligent Systems and Decision Support Systems Natural Language Processing and Computational Applications Cybersecurity and Information Security Emerging Computing Technologies and Digital Systems 2. Information Technology in Education Studies focusing on the design, integration, implementation, and evaluation of digital technologies in teaching and learning environments, including: Computer Science Education and Programming Education Artificial Intelligence in Education (AIED) Educational Data Mining and Learning Analytics Intelligent Tutoring Systems and Adaptive Learning Systems Digital Learning Environments and Online Learning Systems Learning Management Systems (LMS) and E-learning Platforms Immersive Learning Technologies (Virtual Reality, Augmented Reality, Extended Reality) Mobile Learning and Ubiquitous Learning Environments Technology-Enhanced Learning (TEL) and Digital Pedagogy Educational Software and Learning System Development Digital Assessment and Technology-Based Evaluation Systems Computational Thinking, AI Literacy, and Digital Literacy in Education 3. Vocational Technology Education Research examining the integration of computing technologies and digital innovation in vocational, technical, and professional education, including: Curriculum Development in Informatics and Computing Education Competency-Based Training and Digital Skill Development Teaching Factory and Industry 4.0 Learning Environments Smart Learning Environments for Technical and Vocational Education Work-Process Knowledge and Workplace Learning Work-Based Learning and Apprenticeship Systems Industry–Education Collaboration in Computing and Technology Fields Workforce Preparation for Digital and Technology-Driven Industries Digital Literacy and Cybersecurity Education in Vocational Contexts Professional Skills Development for the Digital Economy 4. Innovative Digital Learning and Educational Innovation Research exploring innovative pedagogical approaches, emerging technologies, and new learning ecosystems in digital and technology-enhanced education, including: Innovative Digital Pedagogy and Instructional Design Gamification and Game-Based Learning in Computing and Technology Education Project-Based Learning and Problem-Based Learning Supported by Technology Learning Innovation Using Artificial Intelligence and Intelligent Systems Automation and Smart Learning Technologies in Education Digital Transformation in Education and Training Institutions Emerging Educational Technologies and Future Learning Environments Smart Education Ecosystems and Data-Driven Learning Systems Educational Innovation for Developing Digital Competencies and Future Skills
Arjuna Subject : Ilmu Sosial - Pendidikan
Articles 63 Documents
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Determinants of Employment Social Security Participation among Informal Workers: Evidence from a Cross-Sectional Study in Riau Lira Mufti Azzahri Isnaeni; Putri Ayuni Alayyannur; Prasetyawati
Journal of Vocational, Informatics and Computer Education Vol 4, No 1 (2026): March 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v4i1.599

Abstract

Purpose – Expanding BPJS Ketenagakerjaan coverage in Indonesia remains difficult, especially among informal workers not enrolled through mandatory employer schemes.Scholars note that both cognitive and emotional factors probably shape voluntary enrollment in social protection, but evidence linking these dimensions to employment-based insurance remains scarce. Methods – The research is a type of quantitative research with a cross-sectional design used to explore how knowledge, attitudes, and beliefs correlate with the participation of informal workers in the BPJS Employment program. A cross-sectional survey of 390 purposively sampled informal-sector participants was conducted. Trained enumerators collected data with a structured questionnaire, which was then analysed by multiple linear regression. Findings –Regression findings indicate that knowledge (B = 0.320, p < 0.001), attitude (B = 0.410, p < 0.001), and trust (B = 0.500, p < 0.001) each positively predict enrollment, with trust showing the strongest effect. The global model is significant (F = 28.350, p < 0.001), thus the three variables together account for a meaningful share of the variance. Enhancing informal workers' uptake of BPJS Ketenagakerjaan demands more than spreading facts; it also calls for cultivating supportive attitudes and building trust in the scheme's agencies Research implications – This study points to multi-faceted approaches, education, direct outreach, and reputation strengthening, that respect the unique patterns and challenges of the informal labour sector. Originality – Its approach specifically examines the determinants of informal sector workers' participation in employment social security programs in Indonesia through a comprehensive cross-sectional study design. This research makes a novel contribution by integrating sociodemographic, economic, social security literacy, and occupational risk perception variables into a single empirical analytical framework rarely explored simultaneously in the context of informal workers.
Real-Time Intelligent IoT-Based Drum Brake Temperature Monitoring System Maulana Yusuf Alkahfi; Raka Pratindy; M. Iman Nur Hakim; Nanang Okta Widiandaru
Journal of Vocational, Informatics and Computer Education Vol 4, No 1 (2026): March 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v4i1.601

Abstract

Purpose – This study addresses brake system failures in heavy vehicles caused by excessive thermal buildup in drum brakes. Existing monitoring systems rely on single-parameter sensing and lack early warning capabilities, thereby increasing the risk of brake fade and accidents. This study aims to develop a real-time monitoring system to improve safety. Methods: A Research and Development (R&D) approach was applied, including system design, implementation, and testing. The proposed system integrates a Raspberry Pi 4 Model B, Type K thermocouple, ESP32-C3 Super Mini, and GPS NEO-6M module. The data were transmitted via the Thingspeak IoT platform and displayed on a 7-inch TFT touchscreen. Experimental validation includes thermocouple calibration, GPS speed testing, and IoT latency measurement Findings – The thermocouple achieved a mean absolute error of 7.2°C and a percentage error of 3.4% (96.6% accuracy). The GPS speed measurement showed a 2.6% error (97.4% accuracy). IoT latency ranged from 1.2–2.0 s, with 100% data transmission success. The system reliably triggered alerts when the temperature exceeded 360°C, confirming effective real-time monitoring. Research implications: Limitations include dependence on Internet connectivity, environmental effects on sensors, and scalability challenges. Future work should focus on improving robustness and integrating predictive features. Originality – The developed system demonstrates reliable performance at the prototype level. However, the validation was conducted under controlled conditions using a single sensor and without vehicle load. Therefore, further validation under varying load conditions, road gradients, and multipoint brake measurements is required before practical large-scale deployment.
Design and Implementation of a Real-Time IoT-Based Hydroponic Monitoring System Using Deep Flow Technique with Web Analytics Ramdhan Setiadhi; Imam Taufik; Candra Adipradana; Afifah Nurul Izzati
Journal of Vocational, Informatics and Computer Education Vol 4, No 1 (2026): March 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/voice.v4i1.516

Abstract

Purpose – This study addresses the challenge of maintaining optimal nutrient and environmental conditions in indoor hydroponic cultivation, where temperature, humidity, light intensity, and nutrient concentration interact dynamically. Many existing systems still depend on manual observation or fragmented monitoring, which limits real-time responsiveness and data-driven decision-making. Therefore, this study aims to design and implement a real-time Internet of Things (IoT)-based hydroponic monitoring system using the Deep Flow Technique (DFT) with an integrated architecture for continuous monitoring and analytical interpretation. Methods - An end-to-end IoT monitoring system was developed by integrating sensor hardware, wireless communication, backend processing, and a web-based analytics dashboard. The TDS, DHT21, and BH1750 sensors were connected to an ESP8266 microcontroller for real-time data acquisition and Wi-Fi transmission at 60-second intervals. The backend used NestJS with PostgreSQL storage, and a ReactJS dashboard visualized real-time and historical data. Monitoring will be conducted from late May to mid-June 2025. Findings - The system consistently captured environmental and nutrient data in real time. Nutrient concentration ranged from approximately 400 to 1,100 ppm, temperature from 27–29 °C, humidity from 65–80%, and light intensity from 180–4,780 lx. The data showed consistent temporal patterns and confirmed the system’s capability of monitoring dynamic hydroponic conditions. Research Implications - The system remains limited to monitoring without automated control, pH measurement, sensor drift evaluation, or non-Wi-Fi deployment. Originality – This study contributes an integrated end-to-end IoT architecture that combines real-time sensing, structured data management, and web-based analytics for indoor DFT hydroponics.

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