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A Proposed Framework of Knowledge Management for COVID-19 Mitigation based on Big Data Analytic

Mardhani Riasetiawan, Ahmad Ashari

Abstract


The COVID-19 pandemic has highlighted the importance of effective knowledge management in mitigating the impact of public health crises. Big data analytics can play a critical role in providing insights and informing decision-making during a pandemic. However, the challenges associated with collecting, analyzing, and managing the data, especially with privacy and security concerns, make it a complex task. This paper proposes a knowledge management framework for COVID-19 mitigation using a big data analytics approach. The framework includes a systematic process for data collection, analysis, and dissemination, as well as a set of best practices for knowledge management. Additionally, the framework complies with data protection and privacy regulations. The proposed framework aims to support public health officials and other stakeholders in effectively managing the COVID-19 pandemic by providing timely and accurate information. It can also be adapted and applied to other public health crises and be a useful tool for addressing the challenges associated with big data analytics in the context of public health. The paper presents the proposed framework in detail and provides components of how the framework can be applied to COVID-19 in Indonesia.

 

Doi: 10.28991/ESJ-2023-SPER-015

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Keywords


Knowledge Management; COVID-19; Framework; Big Data Analytic; Mitigation.

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DOI: 10.28991/ESJ-2023-SPER-015

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