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All Journal Briliant: Jurnal Riset dan Konseptual Indonesian Journal of Artificial Intelligence and Data Mining STEAM Engineering : Journal of Science, Technology, Education And Mechanical Engineering
Dian Julianto Wahyudi
S1 Pendidikan Teknik Mesin, Fakultas Teknik, Universitas Negeri Surabaya
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Energy Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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PENGEMBANGAN PERANGKAT PEMBELAJARAN BERBASIS WEB MELALUI INTEGRASI PLATFORM SIPEJAR PADA MATA KULIAH CAD DENGAN PENDEKATAN PROJECT BASED LEARNING Karim, Saifuddin; Pradani, Yayi Febdia; Muhtarom, Imam; Wahyudi, Dian Julianto; Harlin, Harlin
Steam Engineering Vol. 7 No. 1 (2025): STEAM Engineering, Vol. 7, No. 1, September 2025
Publisher : Program Studi Pendidikan Teknik Mesin, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37304/jptm.v7i1.22722

Abstract

This study aims to develop a web-based instructional package integrated with the SIPEJAR platform for the Computer Aided Design (CAD) course at Universitas Negeri Malang, employing a Project Based Learning (PjBL) approach grounded in social constructivism. The development process followed the ADDIE model through the stages of analysis, design, development, implementation, and evaluation. Validation by content and media experts indicated high feasibility with scores above 85%. Implementation in a blended learning setting revealed significant improvements in students’ comprehension (from 16.7% to 73.3%), engagement (from 10% to 83.3%), learning satisfaction (from 16.7% to 76.7%), and motivation, which increased among all respondents. Findings highlight that the developed package is not only technically feasible but also enhances collaborative interaction, critical thinking skills, and student readiness for industry demands. This study contributes to contextual digital learning design in technical education and recommends broader application to similar courses along with the integration of learning analytics for continuous improvement.
Effectiveness of Service Training Based on Education and Training Model On-In-On-In for Dual Skills Program Purnomo, Purnomo; Wahyudi, Dian Julianto; Yoto, Yoto; Dika, Johan Wayan
BRILIANT: Jurnal Riset dan Konseptual Vol 6 No 4 (2021): Volume 6 Nomor 4, November 2021
Publisher : Universitas Nahdlatul Ulama Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (393.349 KB) | DOI: 10.28926/briliant.v6i4.838

Abstract

The focus in this article is to reveal: (1) The purpose of participating in dual skills programs; (2) Effectiveness of In Service Training 1 (In-1); (3) Effectiveness of In Service Training 2 (In-2); (4) Competence Pedagogic and Dual Professional Teacher Skills. Dual Skills Program is the addition of assignments and functions of teachers from normative and adaptive teachers plus the task of teaching productive expertise competencies, carried out for 12 months using the On-In-On-In learning model. Type of case study research with multi-case study design. The results of this study (1) Motivation of teachers to participate in dual skills programs to obtain educator certificates and anticipate shortages of hours; (2) Implementation of In-Service Training 1 is quite effective; (3) Implementation of In Service Training 2 (In-2) is quite effective;  (4) In general On-In-On-In training is quite effective; (5) Teacher competency after training is quite good. Constraints that occur are difficult to divide the teaching time and tasks from training dual skills programs which are quite a lot. To the development of science, especially vocational education, the results of this study are expected to be used as one of the comparative studies on the theory of the effectiveness of On-In-On-In training in obtaining dual related skills: (a) The purpose of participating in a dual expertise program (b) Effectiveness of In Service Training 1 (In-1), (c) Effectiveness of In Service Training 2 (In-2), (d) Competence of Dual Skills Teachers Post-On-In-On-In Training.
Hybrid Reinforcement and Evolutionary Learning Model for Adaptive Pathway Optimization In Computer Networks Education Anggraeni, Sherly Rosa; Wahyudi, Dian Julianto; Silviariza, Waode Yunia; Ro’is, Rachmy Rosyida; Ranggianto, Narandha Arya
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 3 (2025): November 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i3.38398

Abstract

This paper introduces a Hybrid Reinforcement and Evolutionary Learning Model developed to optimize adaptive learning pathways in computer network education. Traditional uniform curricula often struggle to accommodate diverse learner profiles, resulting in knowledge gaps across hierarchical concepts such as OSI layers, routing protocols, and security mechanisms. The proposed model integrates Deep Knowledge Tracing (DKT) with Long Short Term Memory (LSTM) networks for real-time estimation of learners’ knowledge states, Proximal Policy Optimization (PPO) for dynamic sequential content selection, and a Genetic Algorithm Particle Swarm Optimization (GA–PSO) hybrid for global pathway refinement under constraints such as prerequisites and time limits. The model was evaluated using real learner data from an e-learning platform and achieved an average final mastery score of 0.867, quiz accuracy of 0.822, and an F1-score of 0.880 for path recommendations outperforming baseline models such as static curricula (0.740 mastery) and DKT+PPO (0.824 mastery) by 5–17%. Ablation studies validated the synergistic contribution of each component, with the GA–PSO module enhancing optimization efficiency by approximately 10%. Overall, these findings demonstrate that the proposed model offers superior personalization, learning efficiency, and adaptability, marking a significant advancement in AI-driven education for computer networks.
Co-Authors Dika, Johan Wayan harlin, harlin Imam Muhtarom Karim, Saifuddin Narandha Arya Ranggianto Purnomo Purnomo Ro’is, Rachmy Rosyida Sherly Rosa Anggraeni Waode Yunia Silviariza Yayi Febdia Pradani Yoto Yoto, Yoto