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All Journal ADI Journal on Recent Innovation (AJRI) Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi International Transactions on Artificial Intelligence (ITALIC)
Widjaya, Irene Apriani
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Religion Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Other

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Application of Database Normalization in Increasing Data Storage Efficiency Hardini, Marviola; Agarwal, Vertika; Apriani, Desy; Widjaya, Irene Apriani; Setiawaty, Elika; Nurasiah, Nurasiah
International Transactions on Artificial Intelligence Vol. 3 No. 2 (2025): May
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v3i2.799

Abstract

Database normalization is a key process in relational database design that reduces redundancy and ensures data integrity. As data volumes increase, maintaining efficient and consistent storage becomes critical. This study investigates the application of normalization techniques from First Normal Form (1NF) to Third Normal Form (3NF) on a sample inventory database to evaluate their impact on storage efficiency. The process focuses on eliminating data repetition and optimizing table structures to enhance performance. Experimental results show that normalization reduces database size by approximately 30%, significantly minimizing redundancy. Smaller, more organized tables improve storage utilization, especially in large-scale systems. However, normalization can introduce query complexity due to increased joins, potentially affecting execution time. Despite this, the trade-off is considered acceptable given the gains in data integrity and storage optimization. This research emphasizes the value of normalization for scalable and maintainable systems. It also aligns with Sustainable Development Goals (SDGs), particularly Goal 9 (Industry, Innovation, and Infrastructure) and Goal 12 (Responsible Consumption and Production), by promoting efficient digital infrastructure and responsible data management practices. These improvements contribute to more sustainable, cost-effective systems in industries relying on large-scale data, such as e-commerce, healthcare, and finance. In conclusion, normalization is an essential tool for optimizing storage and ensuring data consistency in relational databases. Although performance trade-offs exist, they can be mitigated through indexing and query optimization. The study offers insights for database designers seeking to balance efficiency and system performance in data-intensive environments.
Orange Technology for Humanistic Innovation in Higher Education Wibowo, Shesilia; Widjaya, Irene Apriani; Zanubiya, Jihan; Evans, Richard; Rahardja, Untung
Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi Vol 4 No 2 (2026): March
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/mentari.v4i2.899

Abstract

Amidst the rapid adoption of technology in education, a crucial challenge arises regarding the risk of dehumanizing learning. This study examines Orange Technology as a humanistic innovation approach that seeks to balance digital advancement with human values. Using a qualitative descriptive approach, this research analyzes literature from academic journals and technology education reports, which are then evaluated through a SWOT framework. The analysis results indicate that while Orange Technology holds significant potential to enhance students’ mental well being, digital empathy, and emotional engagement, its implementation faces significant challenges, including limited human resources and inadequate ethical regulations. Therefore, it is concluded that the success of this implementation requires a holistic strategy encompassing investment in human resource training, policy development, and interdisciplinary collaboration. This innovation model has strategic relevance to the Sustainable Development Goals (SDGs), particularly Goal 4 (Quality Education). By focusing on character development and mental well-being, this research contributes to creating an education system that is not only efficient but also inclusive, equitable, and relevant to the holistic needs of future generations.
Machine Learning Approaches for Cybersecurity in Distributed Cloud Infrastructures Prayitno, Dzovani Sandy Putra; Wibowo, Shesilia; Widjaya, Irene Apriani; Martono, Aris; Nanle, Zeze
ADI Journal on Recent Innovation (AJRI) Vol. 7 No. 2 (2026): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v7i2.1417

Abstract

Rapid cloud adoption has transformed enterprise IT infrastructures, but also introduces complex cybersecurity challenges due to the distributed and dynamic nature of cloud environments, increasing exposure to sophisticated cyber threats. This study aims to design and evaluate machine learning-based approaches to enhance cybersecurity in distributed cloud infrastructures, focusing on improving threat detection accuracy, scalability, and operational efficiency in multi-cloud environments. The proposed method employs a layered machine learning framework integrating supervised and unsupervised algorithms to detect intrusions, anomalous behaviors, and policy violations across distributed cloud nodes, supported by real-time data collection and adaptive model training. A methodological illustration indicates that machine learning approaches can achieve higher detection accuracy approximately 90% compared to traditional rule based systems approximately 78%, while reducing false-positive rates from around 22% to 10%, and experimental results further confirm improved detection performance, reduced false positives, and faster response times while maintaining scalability under increasing workloads. These findings demon- strate that machine learning-driven cybersecurity solutions provide a more adaptive, scalable, and effective defense mechanism, supporting secure and sustainable digital transformation in modern cloud environments.
Co-Authors Agarwal, Vertika Desy Apriani Evans, Richard Martono, Aris Marviola Hardini Nanle, Zeze Nurasiah Nurasiah Prayitno, Dzovani Sandy Putra Setiawaty, Elika Untung Rahardja Wibowo, Shesilia Zanubiya, Jihan