DATA GOVERNANCE MECHANISMS IN INDONESIA’S COVID-19 DATA INTEGRATION SYSTEM

Binti azizatun Nafi'ah

Abstract


During a pandemic, policy decisions are made quickly and correctly. The need for COVID-19 data becomes an absolute basis for policymaking. This paper focuses on the mechanism of COVID-19 data management in the national COVID-19  task forces to be able to provide valid and realtime data. Researchers used qualitative analysis, with primary and secondary data collection. Researchers interview 3 information from the ministry of communication and informatics as a public communication team in the task force to accelerate the handling of COVID-19. The results showed that even data management was based on structural, procedural, and relational mechanisms. Structure mechanism has been formed strongly through the task force team from the national to the regions. Procedural data mechanisms, although changing procedures are now at the point of data integration. The relation mechanism shows that the coordination and communication relationship between member task forces has been done quite well where coordination is always done quickly.

Keywords


Mechanisms; Data Governance; COVID-19; Data Integration

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References


Abraham, R., Schneider, J. & Brocke, J.V. (2019). Data governance: A conceptual framework, structured review, and research agenda. International Journal of Information Management 49, 424–438. https://doi.org/10.1016/j.ijinfomgt.2019.07.008

Arif, A., Hellen, S., Arlinta, D. & Piawai, D. (2020, April 23). Urgent Need for Transparent COVID-19 Data. Kompas. Retrieved from https://kompas.id/baca/english/2020/04/23/urgent-need-for-transparent-COVID-19-data/

Buchari, A. (2016). Implementasi e-service pada organisasi publik di bidang pelayanan publik di kelurahan Cibangkong kecamatan batununggal Kota Bandung. Sosiohumaniora. 18(3), 235-239. https://doi.org/10.24198/sosiohumaniora.v18i3

Creswell, J.W. (2010). Research Design: Pendekatan Kualitatif, Kuantitatif, dan Mixed. Yogyakarta: Pustaka Pelajar

Hagmann, J. (2013). Information governance-Beyond the buzz. Records Management Journal, 23(3), 228-240. https://doi.org/10.1108/RMJ-04-2013-0008

Harnani, N., Amijaya, D.H. & Setiadiwibawa, L. (2021). Digital literacy competences in improving the problem-solving skills in facing the industrial revolution 4.0. Sosiohumaniora. 23(2), 290-298. https://doi.org/10.24198/sosiohumaniora.v23i2

Khatri, V. & Brown, C.V. (2010). Designing data governance. Communications of the ACM, 53(1), 148–152. https://doi.org/10.1145/1629175.1629210

Otto, B. (2013). On the evolution of data governance in firms: The case of Johnson & Johnson consumer products North America. In S. S (Ed.). Handbook of data quality (pp. 93–118). Berlin, Heidelberg: Springer.

Rajkumar, R.P. (2020). COVID-19 and mental health: A review of the existing literature. Asian Journal of Psychiatry. 52 (2020) 102066. https://doi.org/10.1016/j.ajp.2020.102066

Shaw, R., Kim, Y. & Hua, J. (2020). Governance, technology, and citizen behavior in a pandemic: Lessons from COVID-19 in East Asia. Progress in Disaster Science. 6 (2020) 100090. http://dx.doi.org/10.1016/j.pdisas.2020.100090

Sun, S., Yu, K., Zhen. & Xiaoting, P. (2020). China empowers Internet hospital to fight against COVID-19. Journal of Infection, S0163-4453(20)30183-3 DOI: 10.1016/j.jinf.2020.03.061Vieira, C.M., Franco, O.H., Restrepo., & Abel, T. (2020). COVID-19: The forgotten priorities of the pandemic. Maturitas. 136 (2020) 38-41. https://doi.org/10.1016/j.maturitas.2020.04.004

World Health Organization. (2020). WHO Coronavirus Disease (COVID-19) Dashboard. June 2, 2020, retrieved from https://COVID-19.o./?gclid=EAIaIQobChMI6p6O1sHj6QIVFSUrCh1oKgeVEAAYASAAEgIRCvD_BwE

Xue, L. Jing, S., Miller, J.C., Sun, W., Li, H., Franco., Hyman, J., & Zhu, H. (2020). A data-driven network model for the emerging COVID-19 epidemics in Wuhan, Toronto, and Italy. Mathematical Biosciences. (pre-proof) https://doi.org/10.1016/j.mbs.2020.108391

Zhou, C., Su, F., Pei, T., Zhang., Du, Y., Luo, B., Cao., Wang, J., Yuan, W., Zhu, Y., Song, C., Chen, J., Xu, J., Li, F., Ma, T., Jiang, L., Yang F., Yi, J., Hu, Y., Liao, Y., & Xiao, H. (2020). COVID-19: Challenges to GIS with Big Data. Geography and Sustainability. 1 (2020) 77-87. https://doi.org/10.1016/j.geosus.2020.03.005




DOI: https://doi.org/10.24198/sosiohumaniora.v23i3.28437

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