Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal PROZIMA (Productivity, Optimization and Manufacturing System Engineering)
Adita Ramadhan, Fadhil
Unknown Affiliation
Industrial & Manufacturing Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Bibliometric Analysis and Data Visualization: Business Intelligence in Digitalization of Supply Chain Management in Healthcare Sector: Analisis Bibliometrik dan Visualisasi Data: Business Intelligence dalam Digitalisasi Manajemen Rantai Pasok pada Sektor Kesehatan Adita Ramadhan, Fadhil; Mansur, Agus
PROZIMA (Productivity, Optimization and Manufacturing System Engineering) Vol. 8 No. 2 (2024): December
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/prozima.v8i2.1728

Abstract

Digital transformation in healthcare supply chain management is increasingly important in addressing operational and distribution efficiency barriers. However, many healthcare institutions have yet to adopt Business Intelligence (BI), causing delays in decision-making, inefficiencies in drug stock management, and waste of resources due to suboptimal distribution. The method used is a bibliometric analysis based on literature observations from major academic databases, with a quantitative approach using VOSviewer to map topic relationships, research trends, and collaboration patterns between researchers. The results of the study confirm that the application of Business Intelligence (BI) in healthcare supply chain management is more dedicated to existing technology-based solutions, such as Artificial Intelligence (AI), Internet of Things (IoT), blockchain, and Big Data, compared to new development methodologies. This study found that although BI can increase efficiency in inventory management by up to 50%, accelerate data-based decision-making by up to 40%, and reduce resource waste by 25%, there are still similarities in policy aspects and obstacles that hinder optimal implementation. In conclusion, the application of BI in the healthcare supply chain must be supported by a structured strategy, including investment in digital infrastructure and workforce training. Further research is recommended to explore policies that can accelerate the implementation of BI in the health sector.
Co-Authors Agus Mansur, Agus