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Emmelia Kristina Hutagaol
Universitas Medika Suherman, Kabupaten Bekasi, Indonesia
Economics, Econometrics & Finance

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Logistics Data Analysis for Increase Efficiency Need in the Effort to Overcome Risk Disaster with Naive Bayes Algorithm Niko Suwaryo; Emmelia Kristina Hutagaol
Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE) Vol 9 No 2 (2026): Sharia Economics
Publisher : Universitas KH. Abdul Chalim Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31538/iijse.v9i2.9852

Abstract

This Logistics Data Processing training aims to improve efficiency in disaster risk management efforts through the application of the Naïve Bayes Algorithm. This program is designed to provide understanding and Skills in effective logistics data management by leveraging machine learning technology. In the context of disaster management, timely and accurate logistics data management is crucial to ensure the efficient distribution of aid and resources. Through a Naïve Bayes algorithm-based approach, this training also supports competency development in Business Intelligence (BI) , which is part of the Digital Business Study Program roadmap. This program prepares participants to process and analyze data using technology. modern Which can increase efficiency And effectiveness operational aspects of disaster risk management. Overall, this training aims to create data-driven solutions applicable to disaster management and to enhance skills in utilizing machine learning algorithms in logistics and broader information management.
Co-Authors Niko Suwaryo