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All Journal Jurnal Konseling dan Pendidikan Journal of Moeslim Research Technik Techno Agriculturae Studium of Research Journal of Biomedical and Techno Nanomaterials Journal of Social Entrepreneurship and Creative Technology Journal of Multidisciplinary Sustainability Asean Synergisia Journal Neosantara Hybrid Learning
Ardi Azhar Nampira
Institute Teknologi Sepuluh November
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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INTERNET OF THINGS (IOT) AND NEW BUSINESS OPPORTUNITIES IN THE CREATIVE SECTOR Loso Judijanto; Haruka Sato; Miku Fujita; Ardi Azhar Nampira
Journal of Social Entrepreneurship and Creative Technology Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jseact.v2i3.2054

Abstract

The rapid growth of the Internet of Things (IoT) has led to significant advancements in various industries, including the creative sector. IoT technology enables the interconnection of devices and systems, allowing for new forms of interaction and automation. However, the potential of IoT to generate new business opportunities within the creative industries has not been fully explored. This research aims to investigate the impact of IoT on the creative sector, focusing on how businesses can leverage IoT to innovate, enhance customer experiences, and streamline operations. The study adopts a qualitative research approach, combining case studies and interviews with industry professionals to explore the current applications of IoT in design, media, entertainment, and the arts. The findings indicate that IoT technologies have the potential to revolutionize the creative sector by enabling personalized experiences, optimizing creative workflows, and creating new revenue streams. Businesses are increasingly adopting IoT to offer interactive experiences, such as smart installations, personalized content, and enhanced product design. The study concludes that IoT can offer substantial business opportunities for companies in the creative sector, especially when it comes to enhancing customer engagement and integrating technology into traditional creative processes.   
AI-Assisted Early Detection of Crop Disease Using Hyperspectral Imaging and Deep Learning in Smallholder Farms Ardi Azhar Nampira; Siti Mariam
Journal of Multidisciplinary Sustainability Asean Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijmsa.v2i3.2305

Abstract

Background. Crop disease is a major threat to smallholder farmers who lack access to timely diagnostic tools. Traditional detection methods rely on visual inspection and often occur too late to prevent significant yield losses. Early detection using hyperspectral imaging and artificial intelligence presents a transformative solution for precision agriculture in resource-limited settings. Purpose. This study aims to develop and evaluate an AI-assisted early detection system for crop diseases using hyperspectral imaging and deep learning, tailored for application in smallholder farms. Method. A convolutional neural network (CNN) model was trained on hyperspectral data collected from five farm sites, with ground-truth annotations by agricultural experts. The model’s performance was evaluated using standard classification metrics, including accuracy, precision, recall, and F1-score. A case study was also conducted to assess real-world applicability. Results. The model achieved an average detection accuracy of 94.2% across all locations, with F1-score reaching 0.92 when using hyperspectral features. Confusion matrix analysis indicated high true positive and true negative rates, confirming reliability. In a field case, early diagnosis enabled targeted intervention and improved yield by 22% compared to prior seasons. Conclusion. The integration of hyperspectral imaging and deep learning offers a practical and scalable solution for early disease detection in smallholder farms. The system demonstrates high accuracy, adaptability, and operational feasibility in real-world conditions. Future work should focus on expanding crop and disease types, user interface development, and integration with mobile and IoT-based platforms.
TEACHER PROFESSIONAL DEVELOPMENT THROUGH IMMERSIVE TECHNOLOGY: AUGMENTED REALITU SIMULATIONS IN HYBRID TEACHER TRAINING Ardi Azhar Nampira; Van Sok; Dara Vann; Widi Harto Purnomo
Journal Neosantara Hybrid Learning Vol. 3 No. 2 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jnhl.v3i2.3048

Abstract

Traditional teacher professional development (PD) models often fail to equip educators with the high-stakes competencies needed for complex classroom management and adaptation in hybrid learning environments. This inadequacy contributes to high early-career attrition, creating a critical need for high-fidelity, scalable practice solutions that bridge the gap between theory and immediate action. This study aimed to assess the causal efficacy of integrating a standardized Augmented Reality (AR) simulation module into hybrid teacher training, quantifying its impact on specific high-stakes teaching competencies (e.g., de-escalation and non-verbal communication). A quasi-experimental, pretest-posttest control group design (N=80) was used over ten weeks. The Experimental Group engaged in continuous AR simulations, while the Control Group received traditional video training. Competency gains were objectively measured using a specialized rubric and analyzed via ANCOVA. The AR intervention demonstrated a highly significant main effect on competency gains (F=42.15, p < 0.001), resulting in a 20.2 point gain, substantially outperforming the 6.8 point gain from passive training. The AR-trained group achieved a 45-second faster De-escalation Time and a 35\% higher score in Non-Verbal Cues, validating the technology’s ability to foster mastery of subtle, complex skills. The AR simulation model is a pedagogically superior and necessary infrastructural component for teacher PD, effectively overcoming the structural limitations of conventional training. Its success in providing objective, embodied, and highly realistic practice provides a new, scalable standard for certifying hybrid teaching competence and mitigating teacher attrition.
Co-Authors Alkautsar Rahman Bruna Costa Carlos Fernandez Chairuddin Chak Sothy Dara Vann Dina Destari Faisal Razak Farida Arinie Felipe Souza Haruka Sato Haziq Idris Jarot Budiasto Justam Justam Khalil Zaman Loso Judijanto Lutpi Samaduri Miku Fujita Ming Pong Nurjannah Nurjannah Rahmi Setiawati Raul Gomez Rina Farah Shazia Akhtar Siti Mariam Siti Shofiah Sofia Lim Som Chai Sulaiman Sulaiman Usman Tahir Van Sok Widi Harto Purnomo