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All Journal IAIC Transactions on Sustainable Digital Innovation (ITSDI) International Journal of Cyber and IT Service Management (IJCITSM) Startupreneur Business Digital (SABDA Journal) Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi Journal of Computer Science and Technology Application BEAM
Asher Nuche
Ijiis Incorporation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Other

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Leadership Configurations Supporting TOGAF-Based Information System Architecture at Jenderal Achmad Yani University Sigit Anggoro; Asher Nuche
International Journal of Cyber ​​and IT Service Management (IJCITSM) Vol. 5 No. 2 (2025): October
Publisher : International Institute for Advanced Science & Technology (IIAST)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ijcitsm.v5i2.201

Abstract

Digital transformation in higher education institutions demands integration between information technology, organizational culture, and adaptive leadership. This study aims to analyze the configuration of leadership styles in supporting The Open Group Architecture Framework (TOGAF) based information system architecture at Jenderal Achmad Yani University (UNJANI), a tertiary institution under the TNI Army Foundation which is building a transformation towards a Smart Military University. This research uses a qualitative approach with a case study method, relying on data from in depth interviews, participant observation and institutional documentation. The research results show that the success of digital transformation in UNJANI is supported by a combination of four leadership styles: military leadership (emphasizing discipline and command), transformational leadership (focusing on vision and empowerment), distributed leadership (emphasizing collaboration and collective decisions), and e-leadership (utilization of information technology in leadership). These four styles play a role in various phases of TOGAF, especially in Architecture Vision, Business Architecture, and Implementation Governance. This study shows that contextual, flexible, and values based leadership is a key factor in the success of information systems architecture in higher education environments.
Innovations in Technology and Data Systems to Strengthen Fisheries Management Rifqi Fahrudin; Royani; Asher Nuche; Elda Diah Safitri
Startupreneur Business Digital (SABDA Journal) Vol. 5 No. 1 (2026): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sabda.v5i1.1045

Abstract

Fisheries management faces critical pressures from overexploitation, climate change, and illegal, unreported, and unregulated (IUU) fishing. Conventional monitoring systems often rely on fragmented and delayed data, which significantly limit effective decision-making. This study examine how emerging digital technologies and advanced data systems enhance governance, transparency, and sustainability in the sector. A mixed-method approach was employed, combining a systematic literature review and a comparative case assessment of technology adoption. The results demonstrate that integrating Electronic Monitoring (EM) and Vessel Monitoring Systems (VMS) can expand monitoring coverage by up to 100% in industrial fleets compared to human observers, while reducing long-term operational costs. Digital reporting platforms (e-logbooks) were found to significantly reduce data transcription errors and shorten the feedback loop between data collection and regulatory action. Furthermore, Artificial Intelligence (AI)-assisted species identification improves the speed of processing catch data from EM footage. However, successful implementation depends on institutional readiness, regulatory alignment, and ensuring equitable digital access for small-scale fishers. This research concludes that while technology holds transformative potential, long-term effectiveness requires integrated governance frameworks and collaborative implementation strategies.
Evaluating the Effectiveness of Machine Learning in Cyber Threat Detection Aulia Khanza; Firdaus Dwi Yulian; Novita Khairunnisa; Natasya Aprila Yusuf; Asher Nuche
CORISINTA Vol 1 No 2 (2024): August
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ysdncf05

Abstract

In today's digital era, cyber threats pose significant challenges to organizations, necessitating more advanced detection methods. This study aims to evaluate the effectiveness of machine learning (ML) techniques in detecting cyber threats, focusing on supervised, unsupervised, and reinforcement learning models. Using datasets such as CICIDS2017, the study trains models including Random Forest, Support Vector Machines (SVM), and Neural Networks. The evaluation is based on accuracy, precision, recall, and F1-score metrics. The results demonstrate that the Random Forest model outperforms others with an accuracy of 92.5\%, a precision of 91.8\%, and an F1-score of 92.4\%. This superior performance highlights its potential for real-time threat detection, as evidenced by a case study where the model effectively identified previously undetected cyber threats in a large technology company's network. However, the study also acknowledges challenges such as data quality and the need for continuous model updates. The findings suggest that integrating ML models into cybersecurity frameworks can significantly enhance threat detection efficiency. Future research should explore combining ML with traditional methods and improving model robustness against adversarial attacks to further advance cybersecurity measures.
Integrating Artificial Intelligence in E-Learning for Organizational Well-Being through Orange Technology Mapping Arthur Simanjuntak; Asep Sutarman; Sheila Aulia Anjani; Asher Nuche
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 1 (2025): October
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i1.706

Abstract

This study conducts a bibliometric analysis of Artificial Intelligence (AI) in e-learning, emphasizing its role in organizational well-being and educational transformation. Using Scopus as the primary database and VOSviewer for visualization, 557 articles published between 2020 and 2025 were analyzed across country, organization, source, author, document, and keyword networks. The results reveal that the United States, United Kingdom, and Germany act as central contributors, while India, Saudi Arabia, Singapore, Hong Kong, and Egypt are rapidly growing in influence. Source analysis identifies leading journals that shape the discourse alongside new outlets that diversify the field. Author and document coupling highlight key works that connect immersive learning environments with pedagogy, while keyword analysis identifies three major clusters related to ethics and governance, motivation and technology enhanced learning, and AI tools such as ChatGPT and generative AI. Overall, the findings show that AI in e-learning has evolved from experimental initiatives into a multidimensional, evidence-based domain. The study concludes by emphasizing how Orange Technology and TRAIVIS frameworks can operationalize ethics by design, support adaptive tutoring, and align AI-driven learning ecosystems with sustainable, well-being-centered educational goals.
Personalized Learning Through Adaptive Technologies in E-Learning Environments Erika Erika; Arthur Simanjuntak; Ika Yuni Purnama; Asher Nuche
Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi Vol 5 No 1 (2026): September
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/mentari.v5i1.1189

Abstract

The rapid development of digital learning technologies has transformed educational practices by enabling more personalized and accessible learning experiences in e-learning environments. As a Background, adaptive technologies have emerged as a promising approach to address diverse learner needs and improve educational accessibility. The Objective of this study is to examine the influence of adaptive technologies on personalized learning experiences and their impact on educational accessibility in e-learning environments. The Method employed a quantitative research approach using a survey distributed to 334 respondents who had experience using e-learning platforms. Data were analyzed using Structural Equation Modeling (SEM) with SmartPLS to evaluate the relationships among the proposed constructs. The Results indicate that adaptive technologies significantly enhance personalized learning experiences by providing tailored learning content, individualized feedback, and flexible learning pathways. Furthermore, the findings reveal that personalized learning experiences have a positive and significant effect on educational accessibility, enabling learners with different backgrounds, abilities, and learning preferences to engage more effectively in the learning process. Adaptive technologies were also found to have a direct positive influence on educational accessibility. In Conclusion, the study demonstrates that the integration of adaptive technologies plays a crucial role in fostering personalized learning and improving educational accessibility within e-learning environments. These findings provide valuable insights for educators, educational institutions, and e-learning developers in designing inclusive and learner-centered digital learning systems that support diverse educational needs and promote equitable access to quality education.
Human-Centered Generative AI for Ethical andSustainable Media Broadcasting Asher Nuche; Rifqi Fahrudin; Royani Royani
Bridging of Emerging AI and Media Broadcasting (BEAM) Vol. 1 No. 2 May (2026): Bridging of Emerging AI and Media Broadcasting
Publisher : Sundara Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The rapid expansion of generative artificial intelligence has transformed media broadcasting by enabling automated content creation, synthetic personalities, real-time production, and personalized audience interaction within decentralized digital ecosystems. However, this transformation also raises critical concerns regarding ethical accountability, audience trust, algorithmic transparency, energy consumption, and the sustainability of AI-driven broadcasting infrastructure. This study aims to examine how human-centered generative AI can support ethical and sustainable media broadcasting while maintaining creativity, journalistic integrity, audience engagement, and environmental responsibility. The method research employs a qualitative conceptual approach based on a structured literature review of recent studies on generative AI, digital media broadcasting, decentralized content systems, AI ethics, and green computing. The analysis is organized around key dimensions, including human-centered design, synthetic media governance, audience personalization, decentralized infrastructure, and energy-efficient AI implementation. The Result findings indicate that human-centered generative AI can enhance broadcasting innovation by improving content efficiency, adaptive storytelling, audience relevance, and interactive media experiences. At the same time, ethical safeguards such as AI labeling, provenance tracking, privacy protection, editorial oversight, and transparent algorithmic governance are essential to prevent misinformation, manipulation, and audience distrust. The study also highlights that sustainable broadcasting re- quires optimized AI models, green data centers, and responsible infrastructure management. This paper concludes that the integration of human-centered, ethical, and sustainable principles is necessary to ensure that generative AI strengthens media broadcasting ecosystems without replacing human values, creativity, and social responsibility.
Co-Authors Arthur Simanjuntak Asep Sutarman Aulia Khanza Elda Diah Safitri Erika Erika Firdaus Dwi Yulian Ika Yuni Purnama Natasya Aprila Yusuf Novita Khairunnisa Rifqi Fahrudin Rifqi Fahrudin Royani Royani Royani Sheila Aulia Anjani Sigit Anggoro