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Optimization of College Academic Decision Making Using Data Visualization and Performance Analysis with Grafana Dashboard Implementation

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This research aims to improve the efficiency of academic decision-making at Dian Nusantara University by applying data visualization technology using Grafana. Although the Academic Information System (SISKA) has facilitated data collection related to students, lecturers, and the Teaching and Learning Process (TLP), the utilization of these data for analysis and evaluation is still not optimal. The main challenge lies in processing the data comprehensively to produce relevant information for academic decision-making. This research was conducted through several stages, from identifying specific academic data needs through discussions with stakeholders, access and extraction of data from the SISKA database, and data integration into Grafana. Furthermore, the collected data is analyzed and visualized using an interactive dashboard that displays trends, patterns, and anomalies related to student and lecturer performance. The results showed that using Grafana could facilitate understanding of academic data, enabling faster, more precise, and data-based decision-making. Clear and intuitive visualizations also help the university monitor PBM effectively and identify areas that need improvement.
Title: Optimization of College Academic Decision Making Using Data Visualization and Performance Analysis with Grafana Dashboard Implementation
Description:
This research aims to improve the efficiency of academic decision-making at Dian Nusantara University by applying data visualization technology using Grafana.
Although the Academic Information System (SISKA) has facilitated data collection related to students, lecturers, and the Teaching and Learning Process (TLP), the utilization of these data for analysis and evaluation is still not optimal.
The main challenge lies in processing the data comprehensively to produce relevant information for academic decision-making.
This research was conducted through several stages, from identifying specific academic data needs through discussions with stakeholders, access and extraction of data from the SISKA database, and data integration into Grafana.
Furthermore, the collected data is analyzed and visualized using an interactive dashboard that displays trends, patterns, and anomalies related to student and lecturer performance.
The results showed that using Grafana could facilitate understanding of academic data, enabling faster, more precise, and data-based decision-making.
Clear and intuitive visualizations also help the university monitor PBM effectively and identify areas that need improvement.

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