<![CDATA[Upstream oil and gas companies face challenges in managing transformer asset data that is vital to operations. The complexity of manual data and transformer information makes it difficult to make optimal decisions. This study aims to develop an effective transformer asset management dashboard using FSN (Fast-Slow-Non Moving) and ABC (Analysis Based Costing) analysis. The research methodology includes identifying system needs, collecting data through observation and interviews, developing solutions using Microsoft Power BI, and testing the User Acceptance Test (UAT). The results showed that the dashboard successfully integrated transformer data with real-time visualization including availability status (2,124 units available, 4,305 ready line units, 2,181 units not ready), ABC-FSN classification (AF 30%, BS 20%, AS 10%, CN 40%), and monthly stock trends. The UAT evaluation of 17 respondents showed an average score of 4.5 with a very appropriate category in the aspects of functional suitability, usability, performance efficiency, reliability, accuracy, visual design, and user satisfaction. Dashboards integrated with the Microsoft 365 ecosystem enable real-time access and support data-driven decision-making for transformer asset management optimization.]]>
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