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The Application of Artificial Intelligence for Anomaly Detection in Big Data Systems for Decision-Making

  • Cut Susan Octiva1*
  • Dikky Suryadi2
  • Loso Judijanto3
  • Mitranikasih Laia4
  • Dedy Irwan5
1 Universitas Amir Hamzah image/svg+xml
2 STMIK Al Muslim
3 IPOSS Jakarta Indonesia
4 Universitas Nias Raya image/svg+xml
5 Universitas Harapan Medan image/svg+xml
* Corresponding Author: Cut Susan Octiva

Abstract

The development of big data technology has generated huge volumes of diverse data, creating challenges in detecting anomalies that could potentially affect decision-making. This research aims to examine the application of artificial intelligence (AI) in detecting anomalies in big data systems to support faster, more accurate and effective decision-making. The approach used includes the integration of machine learning algorithms, such as classification-based detection, clustering, and deep learning, in identifying abnormal patterns in large datasets. The research method involves real-time dataset-based simulations by measuring the performance of AI models using accuracy, precision, recall, and F1-score metrics. The results show that the application of AI can significantly improve the anomaly detection capability compared to conventional methods, with an average accuracy of 92%.

Keywords

Artificial Intelligence Anomalies Big Data

How to Cite

Citation Format
Octiva, C. S., Suryadi, D., Judijanto, L., Laia, M., & Irwan, D. (2024). The Application of Artificial Intelligence for Anomaly Detection in Big Data Systems for Decision-Making. International Journal Software Engineering and Computer Science (IJSECS), 4(3), 983-989. https://doi.org/10.35870/ijsecs.v4i3.3358

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Author Biographies

Cut Susan Octiva, Universitas Amir Hamzah

Universitas Amir Hamzah, Deli Serdang Regency, North Sumatra Province, Indonesia

Dikky Suryadi, STMIK Al Muslim

STMIK Al Muslim, Bekasi Regency, West Java City, Indonesia

Loso Judijanto, IPOSS Jakarta Indonesia

IPOSS Jakarta Indonesia, South Jakarta City, Special Capital Region of Jakarta, Indonesia

Mitranikasih Laia, Universitas Nias Raya

Universitas Nias Raya, South Nias Regency, North Sumatra Province, Indonesia

Dedy Irwan, Universitas Harapan Medan

Universitas Harapan Medan, Medan City, North Sumatra Province, Indonesia

License

Copyright (c) 2024 Cut Susan Octiva, Dikky Suryadi, Loso Judijanto, Mitranikasih Laia, Dedy Irwan

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

This is an open-access journal distributed under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, reproduction, and adaptation in any medium (even commercially), provided appropriate credit is given to the original author(s), a link to the license is provided, and any changes made are indicated. Authors retain copyright without restrictions and grant the journal the right of first publication as well as non-exclusive publishing rights for archiving, indexing, and scholarly dissemination.

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