Big Data Analysis of COVID-19 Mitigation Policy in Indonesia: Democratic, Elitist, and Artificial Intelligence
Rijal Ramdani, Agustiyara Agustiyara, Eko Priyo Purnomo
Abstract
Abstract In response to mitigate COVID-19 local transmission, the Indonesian government has launched several regulative policies. This paper aims to analyze whether the decision-making process of those regulative policies is closed to a democratic or elitist approach and whether the government has adopted Artificial Intelligence (AI) in these processes. We focus on large-scale social distancing (PSBB), homecoming restriction in the Eid Mubarak (Mudik), and new-normal life policy case studies. The research has shown that elite roles are quite dominant with little consideration for public consultation and little attention to the use of AI to consider public preferences. The data were collected from two well-known national online media, which are nasional.kompas.com and tempo.co , while the big data mining and analysis have been applied through N-Vivo 12 software. We argue that although the elitist paradigm can be recognized as an efficient approach in the pandemic and emergency, the decision-makers can accommodate public preferences if they can get insights from online media news with the help of AI technology.