Web-Based Quality Control Dashboard Design for Data Validation and Monitoring: A Case Study of BMKG Instruments
DOI:
https://doi.org/10.21512/emacsjournal.v8i1.13532Keywords:
BMKG, Automatic Weather Station (AWS), Quality Control (QC), Data Visualization, Agile ScrumAbstract
Accurate meteorological data are vital for the operational activities of the Agency for Meteorology, Climatology, and Geophysics (BMKG), specifically for weather forecasting and disaster mitigation. However, Automatic Weather Station (AWS) instruments frequently encounter sensor degradation and technical malfunctions, which compromise data validity. Traditional manual validation is inefficient and prone to human error. This study addresses these gaps by designing a web-based Quality Control (QC) dashboard for real-time AWS data monitoring. Developed using the Laravel framework and PostgreSQL, the system integrates Leaflet.js and Chart.js for interactive spatial and analytical visualization. Using the Agile Scrum methodology, the development process was iteratively refined across eight sprints. Implementation results show a significant improvement in data validation accuracy and a reduction in potential human error. User Acceptance Testing (UAT) with fifteen BMKG specialists confirms high usability, with the system receiving "Strongly Agree" ratings for its efficiency in real-time monitoring and reporting. The practical implications include enhanced data credibility for national climate modeling. This paper concludes that while the dashboard streamlines workflows, future iterations should incorporate automated anomaly detection algorithms. Limitations include a current reliance on static validation thresholds, suggesting a need for machine learning integration in future research.
References
Abdillah, M. Z., Nawangnugraeni, D. A., & Yuniarto, A. H. P. (2021). Geographic information system (GIS) for mapping greenpark using leaflet JS. JTIK (Jurnal Teknik Informatika Kaputama), 5(2), 259-266.
Afif, M., & Meganendra, D. A. (2023). Predictive Maintenance for Automatic Weather Station (AWS) Based on Anomaly Detection Using Autoencoder: A Literature Review. Journal of Computation Physics and Earth Science (JoCPES), 3(2).
AlSalehy, A. S., & Bailey, M. (2025). Improving Time Series Data Quality: Identifying Outliers and Handling Missing Values in a Multilocation Gas and Weather Dataset. Smart Cities, 8(3), 82.
Al-Saqqa, S., Sawalha, S., & AbdelNabi, H. (2020). Agile software development: Methodologies and trends. International Journal of Interactive Mobile Technologies, 14(11).
Benbba, S. (2021). Comparison of D3. js and Chart. js as visualisation tools. Science and Engineering.
Bhagaskoro, A., Al Makky, M., & Huda, H. (2025, February). Development of a Laravel-Based Backend Application Server to Support Farm Animal Information Management at Sein Farm Bandung City. In 2025 International Conference on Advancement in Data Science, E-learning and Information System (ICADEIS) (pp. 1-6). IEEE.
Bhavsar, K., Shah, V., & Gopalan, S. (2020). Scrum: An agile process reengineering in software engineering. International Journal of Innovative Technology and Exploring Engineering, 9(3), 840-848.
Faniriantsoa, R., & Dinku, T. (2022). ADT: The automatic weather station data tool. Frontiers in Climate, 4, 933543.
Handiana, D., Novianti, R., & Sanusi, H. (2020). PENGUJIAN KUALITAS DATA AUTOMATIC WEATHER STATION (AWS) MENGGUNAKAN RELIABILITY DAN CONSISTENCY TEST PADA SISTEM AWS CENTER. Jurnal Widya Climago, 2(2).
Hartono, N., & Erfina, E. (2021). Comparison of stored procedures on relational database management system. Tech-E, 4(2), 8-15.
Hron, M., & Obwegeser, N. (2022). Why and how is Scrum being adapted in practice: A systematic review. Journal of Systems and Software, 183, 111110.
Kodali, N. (2024). Tailwind CSS Integration in Angular: A Technical Overview. International Journal of Innovative Research in Science Engineering and Technology, 13(16652), 10-15680.
Mahmud, D., & Ikbal, M. Z. (2022). The role of etl (extract-transform-load) pipelines in scalable business intelligence: A comparative study of data integration tools. ASRC Procedia: Global Perspectives in Science and Scholarship, 2(1), 89-121.
Patro, B. S., & Bartakke, P. P. (2025, March). Quality Control (QC) and Quality Assurance (QA) Procedures for Meteorological Data from Automatic Weather Stations. In 2025 4th International Conference on Range Technology (ICORT) (pp. 1-6). IEEE.
Priyatna, B., Hananto, A. L., & Nova, M. (2020). Application of UAT (User Acceptance Test) Evaluation Model in Minggon E-Meeting Software Development. Systematics, 2(3), 110-117.
Purwandari, K., Siga, F. A., & Sigalingging, J. W. (2024, July). Quality Control of Automatic Weather Station Data: Study Case in DKI Jakarta. In 2024 IEEE 10th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) (pp. 98-102). IEEE.
Ravi, C. (2025). ETL (Extract, Transform & Load) Automation. International Journal of Emerging Trends in Computer Science and Information Technology, 6(1), 52-55.
Schönig, H. J. (2020). Mastering PostgreSQL 13: Build, administer, and maintain database applications efficiently with PostgreSQL 13. Packt Publishing Ltd.
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