Big Data-Based News Analysis as Input for Special Allocation Fund Policy Management Planning

Abstract

In the modern era, development planning has significantly developed, marked by the emergence of Big Data as an information base for formulating policies. The use of Big Data was increasingly massive during the early days of the COVID-19 pandemic until now because it is considered more effective and efficient in terms of time, cost, and security amidst limited human-physical interaction. Monitoring the implementation of development funded by the Special Allocation Fund (SAF), which has so far been monitored through field visits, has turned into media-based monitoring within the scope of big data. The research aims to present information on public attention, top issues/problems, areas often appearing in media exposure, and top persons related to implementing Physical SAF Assignments, especially on the Thematic of Sustainable Economic Infrastructure Provision (SEIP). The method used in this research is a literature review method with an emphasis on collecting data information through the Intelligence Media Analytics (IMA) system. The approach used is a descriptive qualitative approach, which gives a detailed description of specific individuals or groups about the circumstances that occur. The analysis results show that the issue of refocusing the budget during a pandemic and adjusting the implementation methodology dominates the news about the SEIP thematic SAF. The Province of Bali, the Ministry of Education and Culture, and Nadiem Makarim emerged as the regions that received the most media exposure from the perspective of regions, agencies, and figures.