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Harun Joko Prayitno
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Journal of Deep Learning
Published by Universitas Muhammadiyah Surakarta
ISSN : -     EISSN : 31107591     DOI : 10.23917/jdl
Core Subject : Education, Social,
Education Languange, Linguistic, Communication & Media Social Sciences
The Journal of Deep Learning is dedicated to advancing research on deep learning as a methodological approach in education and AI-based technological development. We emphasize deep learning integrated with artificial intelligent (AI) that fosters meaningful, joyful, and mindful education—rooted in authentic, holistic learning experiences that support students’ spiritual, cognitive, social, and emotional development. 1.⁠ ⁠Fostering Mindful Education Practices We seek contributions that explore how deep learning methodologies can cultivate mindfulness in educational settings. This encompasses promoting self-awareness, reflective practices, metacognition, and emotional regulation to support holistic student development. 2.⁠ ⁠Deep Learning for Meaningful Education We invite articles that examine how deep learning methodologies such as inquiry-based learning, problem-based learning, and project-based learning support students in constructing meaningful knowledge. Studies may focus on developing students’ critical thinking, conceptual understanding, and ability to connect new knowledge with real-life contexts. 3.⁠ ⁠Promoting Joyful Learning Experiences We welcome research on how deep learning approaches can foster joy in learning by encouraging curiosity, creativity, and intrinsic motivation. This includes studies on creating engaging learning environments, designing stimulating learning activities, and supporting positive teacher-student interactions. 4.⁠ ⁠Integration of Technology in Deep Learning Pedagogy We encourage studies that examine how technology such as learning management systems, digital tools, and educational apps can be used to support deep learning methodologies. Submissions should highlight how technology enhances or challenges the implementation of deep, meaningful, joyful, and mindful learning. 5.⁠ ⁠Evaluation and Assessment of Deep Learning Outcomes We welcome research on effective evaluation and assessment strategies aligned with deep learning approaches. This includes authentic assessment, formative assessment, and performance-based tasks that capture students’ understanding, creativity, and reflective abilities.
Arjuna Subject : Ilmu Sosial - Pendidikan
Articles 7 Documents
 1 
Search results for , issue "vol. 1, no. 1, june 2025" : 7 Documents clear
Strategies and Development of the Deep Learning Approach in Vocational High Schools in the Era of Global Computing Joko Budi Utomo; Harun Joko Prayitno; Indri Indri
Journal of Deep Learning Vol. 1, No. 1, June 2025
Publisher : Universitas Muhammadiyah Surakarta in Collaboration with Kemdikdasmen RI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jdl.v1i1.10855

Abstract

The transformation of vocational education in the era of the Industrial Revolution 4.0 demands the integration of learning approaches that go beyond cognitive aspects to include affective and contextual dimensions. This study aims to formulate relevant and applicable strategies for developing a deep learning approach tailored to Vocational High Schools (SMK) in Indonesia. Drawing on the principles of mindful, meaningful, and joyful learning, this research presents a conceptual and practical synthesis that can be implemented in vocational education. The findings indicate that project-based learning, digital reflection, and cross-disciplinary collaboration are effective strategies in fostering students' conceptual understanding and applied skills. Authentic assessments based on portfolios, presentations, and reflective journals are also deemed more representative in measuring deep learning outcomes. On the other hand, teacher capacity-building through transformative pedagogical training, socio-emotional reinforcement, and the formation of Professional Learning Communities is essential for successful implementation. The integration of digital technologies in vocational learning has proven to expand learning spaces and strengthen the connection between schools and industries. This study recommends strengthening policy and infrastructure support to ensure the sustainability of the deep learning approach in SMK as an adaptive, reflective, and relevant learning strategy in the digital era.
Deep Learning: Policies, Concepts, and Implementation in Senior High Schools in Indonesia Puthut Prihantoro; Harun Joko Prayitno; Indri Indri; Dian Artha Kusumaningtyas
Journal of Deep Learning Vol. 1, No. 1, June 2025
Publisher : Universitas Muhammadiyah Surakarta in Collaboration with Kemdikdasmen RI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jdl.v1i1.10964

Abstract

The transformation of education in the era of the Industrial Revolution 4.0 and Society 5.0 demands a more holistic, adaptive, and relevant learning approach aligned with the needs of the 21st century. One emerging approach is deep learning, which, in the educational context, does not refer to artificial intelligence technology, but rather to a learning paradigm that emphasizes deep understanding, critical thinking, collaboration, and the interconnection of cognitive, emotional, and social aspects. This study aims to examine the concept, implementation, and challenges of deep learning in Indonesian education through an analysis of theoretical literature and contextual empirical findings. The study identifies three key pillars that underpin the deep learning approach: mindful learning, meaningful learning, and joyful learning, which work synergistically to create a humanistic and transformative learning experience. The findings show that the implementation of deep learning contributes positively to improving students’ learning motivation, engagement, and reflective thinking skills. Although national policies such as the Merdeka Curriculum have incorporated these principles, practical implementation still faces challenges, particularly concerning teacher competencies and resource availability. Therefore, strengthening educators' capacity and providing adequate learning infrastructure are crucial for the sustainable implementation of deep learning in Indonesia.
Deep Learning: Implementation and Impact in Islamic Junior High Schools Erda Farid Hidayani; Harun Joko Prayitno; Trisakti Handayani
Journal of Deep Learning Vol. 1, No. 1, June 2025
Publisher : Universitas Muhammadiyah Surakarta in Collaboration with Kemdikdasmen RI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jdl.v1i1.11077

Abstract

This study aims to describe the implementation of deep learning strategies at the secondary level within an Islamic educational setting, specifically at SMP Islam Ar‑Rahmah. A descriptive qualitative approach was employed to examine in depth the teaching–learning processes integrated with Islamic values and the school’s sociocultural context. Data were gathered through participatory observation, in‑depth interviews, and the documentation of instructional materials. The findings reveal that deep learning was effectively realized through Problem‑Based Learning (PBL) and Project‑Based Learning (PjBL) in both the natural science (IPA) and social science (IPS) curricula. Students actively engaged in contextualized projects—such as the Socio Project Board initiative and water‑filtration experiments—which fostered critical thinking, collaborative teamwork, and data‑driven decision‑making competencies. Moreover, the integration of religious programming and boarding‑school activities contributed to the development of intrapersonal and interpersonal skills that align with the core values of Pancasila students. Nevertheless, challenges persist, particularly with respect to instructional design and the availability of teacher training. Consequently, systemic support from educational institutions and policymakers is necessary to bolster the sustainable and meaningful implementation of deep learning in Islamic schools.
Developing Deep Learning-Based Worksheets to Improve Higher-Order Thinking Skills in Elementary Social Studies Jatmiko Ananda Chosya; Takiddin Takiddin
Journal of Deep Learning Vol. 1, No. 1, June 2025
Publisher : Universitas Muhammadiyah Surakarta in Collaboration with Kemdikdasmen RI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jdl.v1i1.11156

Abstract

This study aims to develop and evaluate a student worksheet (LKPD) based on deep learning principles to enhance Higher-Order Thinking Skills (HOTS) among fourth-grade students in a madrasah Social Studies context. Employing a Research and Development (R&D) approach with the ADDIE model, the study proceeded through five systematic stages: Analysis, Design, Development, Implementation, and Evaluation. The LKPD was validated by experts in content, language, and media, resulting in an overall validity score of 84.6%, indicating high feasibility for classroom use. In the implementation phase, 30 students participated in pretest and posttest activities. Statistical analysis showed a significant improvement in student learning outcomes, with a t-test significance value of 0.000 and an average N-Gain score of 0.32, classified as moderate. Pedagogical features such as differentiated learning strategies, comic-based apperception, and audio-visual integration through QR codes were embedded in the LKPD to target HOTS domains of analysis, evaluation, and creation. Compared to previous studies, this research extends the application of HOTS-based learning materials into the context of Islamic primary education and demonstrates the pedagogical potential of deep learning in fostering critical and creative thinking. These findings support the broader adoption of multimodal, student-centered instructional designs to meet the demands of 21st-century education.
Implementation of Deep Learning in Education: Towards Mindful, Meaningful, and Joyful Learning Experiences Lukie Masayu Andayanie; Muhammad Syahriandi Adhantoro; Eko Purnomo; Ganno Tribuana Kurniaji; Adi Jufriansah
Journal of Deep Learning Vol. 1, No. 1, June 2025
Publisher : Universitas Muhammadiyah Surakarta in Collaboration with Kemdikdasmen RI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jdl.v1i1.11157

Abstract

The deep learning approach in education has emerged as a promising pedagogical framework for transforming the learning experience to be more holistic, reflective, and aligned with the needs of the twenty‑first century. This study seeks to conceptually explore how the principles of mindful, meaningful, and joyful learning may be integrated through deep learning–based instructional strategies. The methodology comprises a systematic literature review and a conceptual analysis of pertinent academic publications, research reports, and innovative educational practices. Findings reveal that strategies such as personalized learning, project‑based learning, game‑based learning, and community engagement effectively enhance student engagement, critical thinking skills, and intrinsic motivation. Nonetheless, the implementation of deep learning approaches continues to encounter significant challenges, including educator preparedness, limitations in technological infrastructure, and the misalignment of conventional assessment systems. This article recommends the enactment of progressive policy support, the enhancement of professional capacity among educators, and further empirical research to evaluate the efficacy of deep learning strategies across broader contexts. It is anticipated that these findings will contribute to the advancement of more adaptive, inclusive, and empowering educational policies and practices.
Deep Learning vs Differentiated Learning: Learning Innovation in Islamic Boarding School-Based Middle Schools Murwanto Setyo Nugroho; Harun Joko Prayitno; Koesoemo Ratih; Muhammad Samsudin
Journal of Deep Learning Vol. 1, No. 1, June 2025
Publisher : Universitas Muhammadiyah Surakarta in Collaboration with Kemdikdasmen RI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jdl.v1i1.11246

Abstract

This study aims to examine the implementation of deep learning and differentiated learning approaches in Islamic boarding school-based junior high schools (SMP) in order to improve the quality of meaningful, contextual, and humanistic learning. Using a descriptive qualitative approach, data were collected through in-depth interviews, classroom observations, and documentation studies in three Islamic boarding school junior high schools that integrate national and religious curricula. The results of the study indicate that learning strategies such as project-based learning, reflective discussions, and collaborative activities are effective in building conceptual understanding and spiritual values ​​of students. Differentiated learning enables the creation of an inclusive learning environment by adjusting content, processes, and products according to students' learning profiles. Implementation challenges arise in terms of time constraints, dual curriculum burdens, and teacher professional readiness. Authentic project-based and portfolio-based evaluations are more relevant in measuring cognitive, affective, and spiritual competencies holistically. This study recommends the need for educational policies that are more adaptive to the characteristics of Islamic boarding schools, including contextual teacher training, curriculum flexibility, and an inclusive and sustainable evaluation system. These findings confirm that deep learning and differentiated learning have great potential in transforming Islamic boarding school education towards 21st-century learning that is more humanistic, reflective, and transformative.
Visual and Contextual Learning for Deep Learning Education: A Unified Tool for Theory–Practice Integration Itang Enrico Pradana Mahardhika; Harun Joko Prayitno; Indri Indri; Muhammad Ramadhan Fitriyan
Journal of Deep Learning Vol. 1, No. 1, June 2025
Publisher : Universitas Muhammadiyah Surakarta in Collaboration with Kemdikdasmen RI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jdl.v1i1.11556

Abstract

The rapid advancements in artificial intelligence, particularly in deep learning, demand learning methods that are not only theoretical but also applicative and intuitive. This study aims to design and develop an interactive deep learning instructional tool that integrates real-world case studies and dynamic visualizations to enhance users’ conceptual understanding and practical skills. The research employs a development methodology with a mixed-methods approach, adopting the ADDIE model and iterative formative evaluation based on Tessmer’s framework. The developed tool incorporates three primary case studies: image classification, sentiment analysis, and time-series prediction. Each case study features an interactive interface that allows users to explore data, adjust model parameters, and visualize training processes and results in real time. Formative evaluation results demonstrate the tool’s effectiveness in improving learning engagement, understanding of deep learning model mechanisms, and motivation to explore the topic further. These findings underscore the significance of experiential and visualization-based approaches in cutting-edge technology education while contributing to the development of adaptive AI-based learning media.

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