<![CDATA[This study aims to implement Business Intelligence using Microsoft Power BI to support network disturbance monitoring based on trend analysis. The main problem addressed in this research is that network disturbance data has only been used as documentation, resulting in suboptimal monitoring and data analysis processes. The data used in this study consists of historical network disturbance data, including information on disturbance location, type of disturbance, occurrence time, and resolution duration. The research methodology includes data collection, data preprocessing, implementation of a Business Intelligence dashboard, and trend analysis using interactive visualizations in Microsoft Power BI. The developed dashboard consists of Key Performance Indicators (KPI), interactive filters, line charts, pie charts, bar charts, and table visuals to support a more effective and structured network monitoring process. The results show that the implementation of the Business Intelligence dashboard is capable of supporting real-time, interactive, and user-friendly monitoring of network disturbances. The trend analysis results indicate that the number of network disturbances fluctuated each month, with the highest number occurring in August and the lowest in November. In addition, the dominant types of disturbances were identified as Supporting Facilities and Electrical Problems. Based on functional testing and user testing results, all dashboard features performed successfully and were considered effective in supporting monitoring activities and data-driven decision making. ]]>
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