Sentiment Analysis of the New Indonesian Government Policy (Omnibus Law) on Social Media Twitter

Abstract

In this era of modern technology, people are always connected to the internet. Twitter is one of the most developed social media technologies. Countries that adhere to democratic governments usually need opinions from various sources to determine the level of satisfaction and level of acceptance of policies for decision makers, one source that can be used is Twitter. The quality of community satisfaction and the level of acceptance of good policies carried out by the government are important and become benchmarks for maintaining the harmony of state life in Indonesia. In this research study, the level of satisfaction quality and level of acceptance of policies from public reviews will be measured using sentiment analysis, targeting people on Twitter who mention new government policies (omnibus law) in Indonesia. To determine the level of quality of satisfaction and level of acceptance, the Support Vector Machine (SVM) methodology and sentiment analysis were used to classify reviews for the following 8 policy topics in the omnibus law; Increase SMEs, Administration, Area and Land, Employment, Licensing and Investment, Punishment, Research and Innovation, and Taxation. The results showed that topics related to employment were the topics that received the most reviews and negative sentiment from the public, while research and innovation were the topics that were the least reviewed by the public.