Implementation of a Real-Time Leadership Schedule Dashboard for Government Agenda Monitoring
DOI:
https://doi.org/10.47709/brilliance.v6i3.9447Kata Kunci:
agenda monitoring, dashboard, executive schedule, government, real-timeAbstrak
Background: Government institutions require an effective medium for delivering leadership agenda updates quickly, centrally, and transparently. At the Government of Central Papua Province, executive schedule information was previously distributed through messaging applications and internal documents, which made uniform and real-time monitoring difficult for relevant staff. Objective: This study aims to implement a web-based leadership schedule dashboard that supports agenda monitoring through information displays in the governor's office. Methods: The system was developed using the Prototype method through needs analysis, system design, implementation, black-box testing, and deployment. The application uses HTML, CSS, and JavaScript, is hosted through Hostinger for centralized access, and is connected to display monitors through a computer device. Results: The implemented dashboard presents the leadership agenda, date, real-time clock, weather information, and running text in a single interface. Operators can add, update, delete, filter, and export schedule data and configure display settings. Black-box testing of 22 scenarios produced valid results for all tested functions, including operator access, schedule management, periodic data updates, and monitor display. Conclusion: The system improves government agenda monitoring by providing centralized, accessible, and real-time executive schedule information. It supports internal coordination and reduces dependence on fragmented message-based schedule distribution. The monitor-based presentation also enables relevant staff to access current information directly in designated work areas.
Referensi
Bach, B., Freeman, E., Abdul-Rahman, A., Turkay, C., Khan, S., Fan, Y., & Chen, M. (2023). Dashboard design patterns. IEEE Transactions on Visualization and Computer Graphics, 29(1), 342–352. https://doi.org/10.1109/TVCG.2022.3209448
Bachechi, C., Po, L., & Rollo, F. (2022). Big data analytics and visualization in traffic monitoring. Big Data Research, 27, 100292. https://doi.org/10.1016/j.bdr.2021.100292
Chung, M.-H., Yang, Y., Wang, L., Cento, G., Jerath, K., Taank, P., ... Chignell, M. H. (2023). Enhancing cybersecurity situation awareness through visualization: A USB data exfiltration case study. Heliyon, 9(1), e13025. https://doi.org/10.1016/j.heliyon.2023.e13025
Curran, F. C., Carlo, S., & Harris-Walls, K. (2024). Making the data visible: A systematic review of systems-level data dashboards for leadership and policy in education. Review of Educational Research. Advance online publication. https://doi.org/10.3102/00346543241288249
Dashti, M. T., & Basin, D. (2020). A theory of black-box tests. arXiv. https://doi.org/10.48550/arXiv.2006.10387
Hoque, N., & Sultanum, N. (2025). DashGuide: Authoring interactive dashboard tours for guiding dashboard users. Computer Graphics Forum, 44(3), e70107. https://doi.org/10.1111/cgf.70107
Kenigsberg, T. A., Hause, A. M., McNeil, M. M., Nelson, J. C., Shoup, J. A., Goddard, K., ... Weintraub, E. S. (2022). Dashboard development for near real-time visualization of COVID-19 vaccine safety surveillance data in the Vaccine Safety Datalink. Vaccine, 40(22), 3064–3071. https://doi.org/10.1016/j.vaccine.2022.04.010
Patel, A. M., Baxter, W., & Porat, T. (2024). Toward guidelines for designing holistic integrated information visualizations for time-critical contexts: Systematic review. Journal of Medical Internet Research, 26, e58088. https://doi.org/10.2196/58088
Sadhu, S., Solanki, D., Brick, L. A., Nugent, N. R., & Mankodiya, K. (2023). Designing a clinician-centered wearable data dashboard (CarePortal): Participatory design study. JMIR Formative Research, 7, e46866. https://doi.org/10.2196/46866
Schulze, A., Brand, F., Geppert, J., & Böl, G.-F. (2023). Digital dashboards visualizing public health data: A systematic review. Frontiers in Public Health, 11, 999958. https://doi.org/10.3389/fpubh.2023.999958
Setlur, V., Correll, M., Satyanarayan, A., & Tory, M. (2024). Heuristics for supporting cooperative dashboard design. IEEE Transactions on Visualization and Computer Graphics, 30(1), 370–380. https://doi.org/10.1109/TVCG.2023.3327158
Strechen, I., Herasevich, S., Barwise, A., Garcia-Mendez, J., Rovati, L., Pickering, B., ... Herasevich, V. (2024). Centralized multipatient dashboards' impact on intensive care unit clinician performance and satisfaction: A systematic review. Applied Clinical Informatics, 15(3), 414–427. https://doi.org/10.1055/a-2299-7643
Sultanum, N., & Setlur, V. (2025). From instruction to insight: Exploring the functional and semantic roles of text in interactive dashboards. IEEE Transactions on Visualization and Computer Graphics, 31(1), 382–392. https://doi.org/10.1109/TVCG.2024.3456601
Yang, Y., Li, X., Liu, Z., Ke, W., Zu, Q., & Chen, X. (2020). Automated prototype generation from formal requirements model. IEEE Transactions on Reliability, 69(2), 632–656. https://doi.org/10.1109/TR.2019.2934348
Zhang, G., Atasoy, H., & Vasarhelyi, M. A. (2022). Continuous monitoring with machine learning and interactive data visualization: An application to a healthcare payroll process. International Journal of Accounting Information Systems, 46, 100570. https://doi.org/10.1016/j.accinf.2022.100570
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