Article Per Year (5 Year)
p-Index From 2021 - 2026
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This Author published in this journals
All Journal IAIC Transactions on Sustainable Digital Innovation (ITSDI) International Journal of Cyber and IT Service Management (IJCITSM) Startupreneur Business Digital (SABDA Journal) Journal of Computer Science and Technology Application
Asher Nuche
Ijiis Incorporation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering 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.
Co-Authors Arthur Simanjuntak Asep Sutarman Aulia Khanza Elda Diah Safitri Firdaus Dwi Yulian Natasya Aprila Yusuf Novita Khairunnisa Rifqi Fahrudin Royani Sheila Aulia Anjani Sigit Anggoro