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All Journal Aptisi Transactions on Management IAIC Transactions on Sustainable Digital Innovation (ITSDI) ADI Pengabdian kepada Masyarakat Jurnal (ADIMAS Jurnal) Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi International Transactions on Education Technology (ITEE) Journal of Computer Science and Technology Application
Nuche, Asher
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Social Sciences Other

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Ethical Considerations in the Development of AI-Powered Healthcare Assistants Willson, Jett Lee; Nuche, Asher; Widayanti, Riya
International Transactions on Education Technology (ITEE) Vol. 2 No. 2 (2024): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v2i2.566

Abstract

Advances in the field of artificial intelligence (AI) have led to the development of increasingly sophisticated health assistants that can provide support in diagnosis, treatment and general health management. However, as with the use of new technologies in the healthcare context, ethical considerations play an important role in the design, development, and implementation of AI-based health assistants. In this paper, we investigate various ethical considerations associated with the development of AI-based healthcare assistants. We explore issues such as the privacy and security of patient data, transparency and accountability in decision making, and the social and psychological impact of reliance on technology in the healthcare context. We also discuss efforts that can be taken to address these ethical challenges, including the development of appropriate regulatory guidelines, ongoing monitoring of system performance, and education and training for health professionals and end users. By seriously considering ethical aspects in the development of AI-based healthcare assistants, we hope to ensure that this technology can provide maximum benefit to patients while maintaining the ethical and moral values that underlie good healthcare practices.
Pengaruh Sistem Informasi Manajemen Dalam Pembentukan Kinerja Organisasi Bisnis di Indonesia Anugrah, Reksa; Nugroho, Dimas; Nuche, Asher
Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi Vol 2 No 2 (2024): Maret
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/mentari.v2i2.480

Abstract

Dalam dekade terakhir, Sistem Informasi Manajemen (SIM) telah menjadi elemen krusial dalam operasional bisnis di Indonesia, didorong oleh inovasi teknologi, globalisasi, dan pertumbuhan ekonomi berbasis informasi. Sistem informasi manajemen telah berubah dari alat pemrosesan data menjadi sistem pendukung keputusan yang vital untuk lingkungan bisnis yang dinamis. Penelitian ini mengungkap tantangan adaptasi dan integrasi teknologi Sistem Informasi Manajemen di perusahaan-perusahaan Indonesia, terutama dalam inovasi dan pengembangan teknologi informasi. Tujuan penelitian ini adalah menyoroti pengaruh Sistem Informasi Manajemen terhadap organisasi bisnis di Indonesia dan bagaimana sistem tersebut berkontribusi terhadap efisiensi operasional organisasi. 108 data dikumpulkan melalui wawancara dan kuesioner di Lampung, dianalisis menggunakan Uji Z. Hasilnya menunjukkan bahwa terdapat hambatan yang berpengaruh terhadap Sistem Informasi Manajemen dalam meningkatkan kinerja organisasi, dengan memerlukan peningkatan fleksibilitas dalam pola, struktur, dan karakteristik untuk mengikuti perubahan teknologi dan pasar. Penelitian ini merekomendasikan pentingnya komunikasi media untuk penguatan pasar dan seleksi perangkat lunak serta program komputer yang mendukung pertumbuhan dan ekspansi Sistem Informasi Manajemen bagi perusahaan Indonesia untuk efisiensi operasional dan keunggulan kompetitif dan disarankan agar organisasi bisnis meningkatkan fleksibilitas dalam pola, struktur, dan karakteristik Sistem Informasi Manajemen Perusahaan.
Optimizing Decision-Making: Data Analytics Applications in Management Information Systems Gantari, Lumi; Qurotulain, Olivia; Nuche, Asher; Sy, Omar; Erica, Archa
APTISI Transactions on Management (ATM) Vol 8 No 2 (2024): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i2.2202

Abstract

This study delves into integrating data analytics applications within Management Information Systems (MIS), exploring their impact on decision-making processes in organizational settings. The discussion synthesizes qualitative and quantitative methodologies, presenting insights from scholarly literature, surveys, and interviews. Scholarly discourse highlights the transformative potential of data analytics tools in facilitating informed decision-making, aligning with practical applications showcased in empirical studies. However, inherent challenges surface, primarily concerning data quality, as revealed by 62\% of respondents, underscoring the need for organizations to address these obstacles. Despite challenges, substantial adoption rates of data analytics tools (78\%) affirm their growing recognition in decision-making within diverse industries. Reported enhancements in operational efficiency (35\%) and competitive advantage (22\%) among organizations leveraging data analytics validate their efficacy in driving organizational performance metrics within MIS. Further research should address ethical implications, longitudinal analyses of data analytics efficacy, and interdisciplinary collaborations exploring the nexus between data analytics and managerial decision-making. This study is a foundational step, providing empirical evidence and future research trajectories essential for organizations aiming to optimize decision-making through data analytics applications within Management Information Systems.
Optimizing Efficiency Through Sustainable Strategies: The Role of Management and Monitoring in Achieving Goals Sy , Omar; Carlos Rodriguez, Juan; Nuche, Asher
APTISI Transactions on Management (ATM) Vol 8 No 2 (2024): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i2.2257

Abstract

In today's rapidly evolving business landscape, efficiency is a critical aspect for organizations aiming to remain competitive and sustainable. This research explores the important roles of management and monitoring in achieving organizational goals while prioritizing sustainable practices. Effective management serves as a primary driver in formulating, implementing, and overseeing initiatives to enhance efficiency while also reducing negative impacts on the environment and society. Strong monitoring enables organizations to assess the effectiveness of sustainable initiatives, identify areas needing improvement, and track progress toward established goals. Through systematic data collection and analysis, monitoring facilitates informed decision-making, thereby enhancing the organization's ability to align actions with its sustainability objectives. The research findings indicate that effective decision-making, accurate performance measurement, good strategic planning, and strong monitoring mechanisms significantly influence organizational productivity and the achievement of company goals. By reinforcing management practices and monitoring mechanisms, organizations can optimize operational efficiency and achieve strategic goals sustainably.
Penerapan Outcome-Based Education dalam Pengajaran Manajemen Pemasaran dan Studi Benchmarking: Penerapan Outcome Based Education dalam Pengajaran Manajemen Pemasaran dan Studi Benchmarking Magdalena, Lena; Sutrisna; Nuche, Asher; Asri; Aprillia, Ariesya; Setiawan, Sandy
ADI Pengabdian Kepada Masyarakat Vol. 5 No. 2 (2025): ADI Pengabdian Kepada Masyarakat
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/adimas.v5i2.1220

Abstract

In the era of globalization, higher education faces significant challenges in ensuring the quality and relevance of graduates at the international level. One strategy to enhance global competitiveness is through international benchmarking, a process of comparing institutional performance with global standards or leading institutions in the field. International benchmarking goes beyond academic outcomes it also includes curriculum development, teaching methods, and the improvement of student skills to meet global industry demands. Within the framework of Outcome-Based Education (OBE), the achievement of learning outcomes is a key indicator of a program’s success. OBE emphasizes the results students must attain after completing their studies, including technical skills, critical thinking abilities, and professional competencies. International benchmarking plays a crucial role in designing OBE-based curricula to ensure graduates possess internationally recognized competencies. However, its implementation poses several challenges, such as limited resources, institutional readiness to align with global standards, and difficulties in accessing valid and relevant comparative data. This study aims to explore the impact of international benchmarking on the achievement of learning outcomes within the OBE framework by examining case studies and analyzing data from institutions that have implemented benchmarking practices. The study employs case studies and data analysis from institutions that have implemented international benchmarking practices. The findings are expected to provide strategic insights into the effectiveness of benchmarking in enhancing higher education quality. Additionally, the study aims to identify adaptive and sustainable implementation strategies for educational institutions in Indonesia.
Evaluating the Effectiveness of Machine Learning in Cyber Threat Detection Khanza, Aulia; Yulian, Firdaus Dwi; Khairunnisa, Novita; Yusuf, Natasya Aprila; Nuche, Asher
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 Simanjuntak, Arthur; Sutarman, Asep; Anjani, Sheila Aulia; Nuche, Asher
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 Anjani, Sheila Aulia Anugrah, Reksa Aprillia, Ariesya Arthur Simanjuntak Asri Carlos Rodriguez, Juan Dimas Nugroho Erica, Archa Gantari, Lumi Khairunnisa, Novita Khanza, Aulia Lena Magdalena, Lena Qurotulain, Olivia Riya Widayanti Setiawan, Sandy Sutarman, Asep Sutrisna Sy , Omar Sy, Omar Willson, Jett Lee Yulian, Firdaus Dwi Yusuf, Natasya Aprila