Interoperable organisations in crisis: Supporting data surveillance during Indonesia's COVID-19 pandemic

This study aims to assess the interoperability of Indonesian government organizations in implementing COVID-19 data integration. The COVID-19 pandemic has created a need for fast, accurate, and effective data transmission to control the COVID-19 outbreak in Indonesia. This study uses the Qualitative Data Software Analysis (QDSA) approach with the help of the Nvivo data analysis software . Secondary data sources are placed as primary data with the consideration of valid data with transparent sources. This study utilizes big data as primary data, with structured, semi-structured, and unstructured data properties. Structured data collection through the official website portal of the Central Government and Provincial Government and the COVID-19 Task Force Report Document. Unstructured data is mined from information on National Mass Media articles, which are limited by the period and topic of the problem. The study results show that identification related to data management and surveillance of COVID-19 data in Indonesia in recording and reporting COVID-19 cases is computerized through online applications. The TC-All Record 19 application is part of a strategy to improve the integration of collaborative data sharing between organizations. However, an excellent organizational interoperability maturity does not support the implementation of data sharing. This condition can be seen from data transmission between the central government and regional governments, which have a high gap in the quality of COVID-19 data surveillance. Organizational interoperability is assessed using Business Processes, Policies, Governance, Architecture, Economics, and Regulations/Laws.