Executive Information System Berbasis Scrum untuk Monitoring dan Visualisasi Penyebaran Demam Berdarah Dengue (DBD)
Keywords:
Demam Berdarah Dengue, Sistem Informasi Eksekutif, Surveilans Kesehatan Masyarakat, Metode Scrum
Abstract
The Executive Information System (EIS) is designed to provide strategic reports that assist executives in making decisions quickly, accurately, and based on data. In the context of public health, the EIS plays a vital role in monitoring and controlling the spread of vector-borne infectious diseases such as Dengue Hemorrhagic Fever (DHF). This study aims to design and develop an initial web-based prototype of an EIS capable of detecting and monitoring the spread of DHF in Indonesia through interactive data visualization, statistical analysis, and informative geographic mapping. The system development adopted the Scrum approach, consisting of several stages: product backlog, sprint planning, daily scrum, sprint review, and sprint retrospective. The results indicate that all sprints were completed on schedule, producing a prototype that displays case distribution data, temporal trends, and high-risk areas equipped with features such as filtering, drill-down analysis, and data importing. However, this study remains at the initial design stage; therefore, user validation testing has not yet been conducted. This stage is planned for future research through Usability Testing (System Usability Scale) and Decision-Making Effectiveness Evaluation to assess the level of user acceptance, ease of use, and the system’s impact on executive decision-making in the field of public health.
References
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Alves, D. ; G. P. ; C. C. (2020). Interactive dashboards for data analysis in public health: A systematic review. Journal of Biomedical Informatics, 107(103450).
Anggraini Ningrum, D. N., Li, Y.-C. (Jack), Hsu, C.-Y., Solihuddin Muhtar, M., & Pandu Suhito, H. (2024). Artificial Intelligence Approach for Severe Dengue Early Warning System. https://doi.org/10.3233/SHTI231091
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Hidalgo, E. S. (2019). Adapting the scrum framework for agile project management in science: case study of a distributed research initiative. Heliyon, 5(3), e01447. https://doi.org/10.1016/j.heliyon.2019.e01447
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Hyzy, M., Bond, R., Mulvenna, M., Bai, L., Dix, A., Leigh, S., & Hunt, S. (2022). System Usability Scale Benchmarking for Digital Health Apps: Meta-analysis. JMIR MHealth and UHealth, 10(8), e37290. https://doi.org/10.2196/37290
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Kortum, P. ; B. A. (2018). Usability ratings for everyday products measured with the System Usability Scale (SUS). International Journal of Human–Computer Interaction, 34(3).
Laing, S. ; W. S. A. ; C. E. (2021). Improved preventive care clinical decision-making efficiency: Evaluation of a digital decision-support tool. BMC Medical Informatics and Decision Making, 21(195).
Leivadeas, A., Falkner, M., Lambadaris, I., & Kesidis, G. (2017). Optimal virtualized network function allocation for an SDN enabled cloud. Computer Standards & Interfaces, 54, 266–278. https://doi.org/10.1016/j.csi.2017.01.001
Manirambona, E., Okesanya, O. J., Olaleke, N. O., Oso, T. A., & Lucero-Prisno, D. E. (2024). Evolution and implications of SARS-CoV-2 variants in the post-pandemic era. Discover Public Health, 21(1), 16. https://doi.org/10.1186/s12982-024-00140-x
Marai, G. E. (2018). Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization. IEEE Transactions on Visualization and Computer Graphics, 24(1), 913–922. https://doi.org/10.1109/TVCG.2017.2744459
Mishra, A., & Alzoubi, Y. I. (2023). Structured software development versus agile software development: a comparative analysis. International Journal of System Assurance Engineering and Management, 14(4), 1504–1522. https://doi.org/10.1007/s13198-023-01958-5
Morales, J., Silva-Aravena, F., & Saez, P. (2024). Reducing Waiting Times to Improve Patient Satisfaction: A Hybrid Strategy for Decision Support Management. Mathematics, 12(23), 3743. https://doi.org/10.3390/math12233743
Odunayo Josephine Akindote, Abimbola Oluwatoyin Adegbite, Adedolapo Omotosho, Anthony Anyanwu, & Chinedu Paschal Maduka. (2024). EVALUATING THE EFFECTIVENESS OF IT PROJECT MANAGEMENT IN HEALTHCARE DIGITALIZATION: A REVIEW. International Medical Science Research Journal, 4(1), 37–50. https://doi.org/10.51594/imsrj.v4i1.698
O’Reilly, K. M., Hendrickx, E., Kharisma, D. D., Wilastonegoro, N. N., Carrington, L. B., Elyazar, I. R. F., … Brady, O. J. (2019). Estimating the burden of dengue and the impact of release of wMel Wolbachia-infected mosquitoes in Indonesia: a modelling study. BMC Medicine, 17(1), 172. https://doi.org/10.1186/s12916-019-1396-4
Parveen, S., Riaz, Z., Saeed, S., Ishaque, U., Sultana, M., Faiz, Z., … Marium, A. (2023). Dengue hemorrhagic fever: a growing global menace. Journal of Water and Health, 21(11), 1632–1650. https://doi.org/10.2166/wh.2023.114
Piras, G., Agostinelli, S., & Muzi, F. (2025). Smart Buildings and Digital Twin to Monitoring the Efficiency and Wellness of Working Environments: A Case Study on IoT Integration and Data-Driven Management. Applied Sciences, 15(9), 4939. https://doi.org/10.3390/app15094939
Polonsky, J. A., Baidjoe, A., Kamvar, Z. N., Cori, A., Durski, K., Edmunds, W. J., … Jombart, T. (2019). Outbreak analytics: a developing data science for informing the response to emerging pathogens. Philosophical Transactions of the Royal Society B: Biological Sciences, 374(1776), 20180276. https://doi.org/10.1098/rstb.2018.0276
Ridhani, D., Krismadinata, Novaliendry, D., Ambiyar, & Effendi, H. (2024). Development of An Intelligent Learning Evaluation System Based on Big Data. Data and Metadata, 3. https://doi.org/10.56294/dm2024.569
Rotejanaprasert, C., Areechokchai, D., & Maude, R. J. (2024). Two-step spatiotemporal anomaly detection corrected for lag reporting time with application to real-time dengue surveillance in Thailand. BMC Medical Research Methodology, 24(1), 10. https://doi.org/10.1186/s12874-024-02141-5
Santillana, M., Nguyen, A. T., Louie, T., Zink, A., Gray, J., Sung, I., & Brownstein, J. S. (2016). Cloud-based Electronic Health Records for Real-time, Region-specific Influenza Surveillance. Scientific Reports, 6(1), 25732. https://doi.org/10.1038/srep25732
Sarker, R., Roknuzzaman, A. S. M., Emon, F. A., Dewan, S. M. R., Hossain, Md. J., & Islam, Md. R. (2024). A perspective on the worst ever dengue outbreak 2023 in Bangladesh: What makes this old enemy so deadly, and how can we combat it? Health Science Reports, 7(5). https://doi.org/10.1002/hsr2.2077
Sauro, J. L. J. R. (2016). Quantifying the User Experience: Practical Statistics for User Research (2nd ed.). Cambridge, MA: Morgan Kaufmann.
Srivastava, P., & Jain, S. (2017). A leadership framework for distributed self-organized scrum teams. Team Performance Management: An International Journal, 23(5/6), 293–314. https://doi.org/10.1108/TPM-06-2016-0033
Sylvestre, E., Joachim, C., Cécilia-Joseph, E., Bouzillé, G., Campillo-Gimenez, B., Cuggia, M., & Cabié, A. (2022). Data-driven methods for dengue prediction and surveillance using real-world and Big Data: A systematic review. PLOS Neglected Tropical Diseases, 16(1), e0010056. https://doi.org/10.1371/journal.pntd.0010056
Wang, W., Qiu, L., Kim, D., & Benbasat, I. (2016). Effects of rational and social appeals of online recommendation agents on cognition- and affect-based trust. Decision Support Systems, 86, 48–60. https://doi.org/10.1016/j.dss.2016.03.007
Winter, D. ; D. D. (2023). Paired-sample statistical tests for comparing user performance before and after intervention. Behaviour & Information Technology, 42(3).
Wu, D. T. Y., Vennemeyer, S., Brown, K., Revalee, J., Murdock, P., Salomone, S., … Hanke, S. P. (2019). Usability Testing of an Interactive Dashboard for Surgical Quality Improvement in a Large Congenital Heart Center. Applied Clinical Informatics, 10(05), 859–869. https://doi.org/10.1055/s-0039-1698466
Zheng, X., Hu, X., Arista, R., Lu, J., Sorvari, J., Lentes, J., … Kiritsis, D. (2024). A semantic-driven tradespace framework to accelerate aircraft manufacturing system design. Journal of Intelligent Manufacturing, 35(1), 175–198. https://doi.org/10.1007/s10845-022-02043-7
Alves, D. ; G. P. ; C. C. (2020). Interactive dashboards for data analysis in public health: A systematic review. Journal of Biomedical Informatics, 107(103450).
Anggraini Ningrum, D. N., Li, Y.-C. (Jack), Hsu, C.-Y., Solihuddin Muhtar, M., & Pandu Suhito, H. (2024). Artificial Intelligence Approach for Severe Dengue Early Warning System. https://doi.org/10.3233/SHTI231091
Azonuche, T. I., & Enyejo, J. O. (2025). Adaptive Risk Management in Agile Projects Using Predictive Analytics and Real-Time Velocity Data Visualization Dashboard. International Journal of Innovative Science and Research Technology, 2032–2047. https://doi.org/10.38124/ijisrt/25apr2002
Badgeley, M. A., Shameer, K., Glicksberg, B. S., Tomlinson, M. S., Levin, M. A., McCormick, P. J., … Dudley, J. T. (2016). EHDViz: clinical dashboard development using open-source technologies. BMJ Open, 6(3), e010579. https://doi.org/10.1136/bmjopen-2015-010579
Baxter, D., & Turner, N. (2023). Why Scrum works in new product development: the role of social capital in managing complexity. Production Planning & Control, 34(13), 1248–1260. https://doi.org/10.1080/09537287.2021.1997291
Fagherazzi, G. ; R. P. (2020). Digital technologies for chronic disease management: From telehealth to the executive dashboard. The Lancet Digital Health, 2(12).
Faridah, L., Fauziah, N., Agustian, D., Mindra Jaya, I. G. N., Eka Putra, R., Ekawardhani, S., … Watanabe, K. (2022). Temporal Correlation Between Urban Microclimate, Vector Mosquito Abundance, and Dengue Cases. Journal of Medical Entomology, 59(3), 1008–1018. https://doi.org/10.1093/jme/tjac005
Ghorbani, R., Reinders, M. J. T., & Tax, D. M. J. (2024). Personalized anomaly detection in PPG data using representation learning and biometric identification. Biomedical Signal Processing and Control, 94, 106216. https://doi.org/10.1016/j.bspc.2024.106216
Gibb, R., Colón-González, F. J., Lan, P. T., Huong, P. T., Nam, V. S., Duoc, V. T., … Lowe, R. (2023). Interactions between climate change, urban infrastructure and mobility are driving dengue emergence in Vietnam. Nature Communications, 14(1), 8179. https://doi.org/10.1038/s41467-023-43954-0
Gmira, M., Gendreau, M., Lodi, A., & Potvin, J.-Y. (2021). Tabu search for the time-dependent vehicle routing problem with time windows on a road network. European Journal of Operational Research, 288(1), 129–140. https://doi.org/10.1016/j.ejor.2020.05.041
Groseclose, S. L., & Buckeridge, D. L. (2017). Public Health Surveillance Systems: Recent Advances in Their Use and Evaluation. Annual Review of Public Health, 38(1), 57–79. https://doi.org/10.1146/annurev-publhealth-031816-044348
Harapan, H., Michie, A., Mudatsir, M., Sasmono, R. T., & Imrie, A. (2019). Epidemiology of dengue hemorrhagic fever in Indonesia: analysis of five decades data from the National Disease Surveillance. BMC Research Notes, 12(1), 350. https://doi.org/10.1186/s13104-019-4379-9
Hess, A., Davis, J. K., & Wimberly, M. C. (2018). Identifying Environmental Risk Factors and Mapping the Distribution of West Nile Virus in an Endemic Region of North America. GeoHealth, 2(12), 395–409. https://doi.org/10.1029/2018GH000161
Hidalgo, E. S. (2019). Adapting the scrum framework for agile project management in science: case study of a distributed research initiative. Heliyon, 5(3), e01447. https://doi.org/10.1016/j.heliyon.2019.e01447
Hyzy, M. ; B. R. ; M. M. ; B. L. ; D. A. ; L. S. ; H. S. (2022). System Usability Scale (SUS) benchmarking for digital health apps: A case study. JMIR MHealth and UHealth, 10(8).
Hyzy, M., Bond, R., Mulvenna, M., Bai, L., Dix, A., Leigh, S., & Hunt, S. (2022). System Usability Scale Benchmarking for Digital Health Apps: Meta-analysis. JMIR MHealth and UHealth, 10(8), e37290. https://doi.org/10.2196/37290
Kemp, N. T. (2021a). A Tutorial on Electrochemical Impedance Spectroscopy and Nanogap Electrodes for Biosensing Applications. IEEE Sensors Journal, 21(20), 22232–22245. https://doi.org/10.1109/JSEN.2021.3084284
Kemp, N. T. (2021b). A Tutorial on Electrochemical Impedance Spectroscopy and Nanogap Electrodes for Biosensing Applications. IEEE Sensors Journal, 21(20), 22232–22245. https://doi.org/10.1109/JSEN.2021.3084284
Kortum, P. ; B. A. (2018). Usability ratings for everyday products measured with the System Usability Scale (SUS). International Journal of Human–Computer Interaction, 34(3).
Laing, S. ; W. S. A. ; C. E. (2021). Improved preventive care clinical decision-making efficiency: Evaluation of a digital decision-support tool. BMC Medical Informatics and Decision Making, 21(195).
Leivadeas, A., Falkner, M., Lambadaris, I., & Kesidis, G. (2017). Optimal virtualized network function allocation for an SDN enabled cloud. Computer Standards & Interfaces, 54, 266–278. https://doi.org/10.1016/j.csi.2017.01.001
Manirambona, E., Okesanya, O. J., Olaleke, N. O., Oso, T. A., & Lucero-Prisno, D. E. (2024). Evolution and implications of SARS-CoV-2 variants in the post-pandemic era. Discover Public Health, 21(1), 16. https://doi.org/10.1186/s12982-024-00140-x
Marai, G. E. (2018). Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization. IEEE Transactions on Visualization and Computer Graphics, 24(1), 913–922. https://doi.org/10.1109/TVCG.2017.2744459
Mishra, A., & Alzoubi, Y. I. (2023). Structured software development versus agile software development: a comparative analysis. International Journal of System Assurance Engineering and Management, 14(4), 1504–1522. https://doi.org/10.1007/s13198-023-01958-5
Morales, J., Silva-Aravena, F., & Saez, P. (2024). Reducing Waiting Times to Improve Patient Satisfaction: A Hybrid Strategy for Decision Support Management. Mathematics, 12(23), 3743. https://doi.org/10.3390/math12233743
Odunayo Josephine Akindote, Abimbola Oluwatoyin Adegbite, Adedolapo Omotosho, Anthony Anyanwu, & Chinedu Paschal Maduka. (2024). EVALUATING THE EFFECTIVENESS OF IT PROJECT MANAGEMENT IN HEALTHCARE DIGITALIZATION: A REVIEW. International Medical Science Research Journal, 4(1), 37–50. https://doi.org/10.51594/imsrj.v4i1.698
O’Reilly, K. M., Hendrickx, E., Kharisma, D. D., Wilastonegoro, N. N., Carrington, L. B., Elyazar, I. R. F., … Brady, O. J. (2019). Estimating the burden of dengue and the impact of release of wMel Wolbachia-infected mosquitoes in Indonesia: a modelling study. BMC Medicine, 17(1), 172. https://doi.org/10.1186/s12916-019-1396-4
Parveen, S., Riaz, Z., Saeed, S., Ishaque, U., Sultana, M., Faiz, Z., … Marium, A. (2023). Dengue hemorrhagic fever: a growing global menace. Journal of Water and Health, 21(11), 1632–1650. https://doi.org/10.2166/wh.2023.114
Piras, G., Agostinelli, S., & Muzi, F. (2025). Smart Buildings and Digital Twin to Monitoring the Efficiency and Wellness of Working Environments: A Case Study on IoT Integration and Data-Driven Management. Applied Sciences, 15(9), 4939. https://doi.org/10.3390/app15094939
Polonsky, J. A., Baidjoe, A., Kamvar, Z. N., Cori, A., Durski, K., Edmunds, W. J., … Jombart, T. (2019). Outbreak analytics: a developing data science for informing the response to emerging pathogens. Philosophical Transactions of the Royal Society B: Biological Sciences, 374(1776), 20180276. https://doi.org/10.1098/rstb.2018.0276
Ridhani, D., Krismadinata, Novaliendry, D., Ambiyar, & Effendi, H. (2024). Development of An Intelligent Learning Evaluation System Based on Big Data. Data and Metadata, 3. https://doi.org/10.56294/dm2024.569
Rotejanaprasert, C., Areechokchai, D., & Maude, R. J. (2024). Two-step spatiotemporal anomaly detection corrected for lag reporting time with application to real-time dengue surveillance in Thailand. BMC Medical Research Methodology, 24(1), 10. https://doi.org/10.1186/s12874-024-02141-5
Santillana, M., Nguyen, A. T., Louie, T., Zink, A., Gray, J., Sung, I., & Brownstein, J. S. (2016). Cloud-based Electronic Health Records for Real-time, Region-specific Influenza Surveillance. Scientific Reports, 6(1), 25732. https://doi.org/10.1038/srep25732
Sarker, R., Roknuzzaman, A. S. M., Emon, F. A., Dewan, S. M. R., Hossain, Md. J., & Islam, Md. R. (2024). A perspective on the worst ever dengue outbreak 2023 in Bangladesh: What makes this old enemy so deadly, and how can we combat it? Health Science Reports, 7(5). https://doi.org/10.1002/hsr2.2077
Sauro, J. L. J. R. (2016). Quantifying the User Experience: Practical Statistics for User Research (2nd ed.). Cambridge, MA: Morgan Kaufmann.
Srivastava, P., & Jain, S. (2017). A leadership framework for distributed self-organized scrum teams. Team Performance Management: An International Journal, 23(5/6), 293–314. https://doi.org/10.1108/TPM-06-2016-0033
Sylvestre, E., Joachim, C., Cécilia-Joseph, E., Bouzillé, G., Campillo-Gimenez, B., Cuggia, M., & Cabié, A. (2022). Data-driven methods for dengue prediction and surveillance using real-world and Big Data: A systematic review. PLOS Neglected Tropical Diseases, 16(1), e0010056. https://doi.org/10.1371/journal.pntd.0010056
Wang, W., Qiu, L., Kim, D., & Benbasat, I. (2016). Effects of rational and social appeals of online recommendation agents on cognition- and affect-based trust. Decision Support Systems, 86, 48–60. https://doi.org/10.1016/j.dss.2016.03.007
Winter, D. ; D. D. (2023). Paired-sample statistical tests for comparing user performance before and after intervention. Behaviour & Information Technology, 42(3).
Wu, D. T. Y., Vennemeyer, S., Brown, K., Revalee, J., Murdock, P., Salomone, S., … Hanke, S. P. (2019). Usability Testing of an Interactive Dashboard for Surgical Quality Improvement in a Large Congenital Heart Center. Applied Clinical Informatics, 10(05), 859–869. https://doi.org/10.1055/s-0039-1698466
Zheng, X., Hu, X., Arista, R., Lu, J., Sorvari, J., Lentes, J., … Kiritsis, D. (2024). A semantic-driven tradespace framework to accelerate aircraft manufacturing system design. Journal of Intelligent Manufacturing, 35(1), 175–198. https://doi.org/10.1007/s10845-022-02043-7
Published
2025-11-25
How to Cite
Rohmah, S., Trivilia, I., Khumaida, R., & Setiawan, R. (2025, November 25). Executive Information System Berbasis Scrum untuk Monitoring dan Visualisasi Penyebaran Demam Berdarah Dengue (DBD). Seminar Nasional Penelitian Dan Pengabdian Kepada Masyarakat 2025, 4(1), 22-30. https://doi.org/https://doi.org/10.35960/snppkm.v4i1.1369
Section
Penelitian
This work is licensed under a Creative Commons Attribution 4.0 International License.
