Dynamics of Indonesian Public Opinion on the Rohingya Crisis in Time Perspective Using Traditional Machine Learning and Deep Learning

Abstract

The Rohingya are an ethnic minority who currently still face persecution and discrimination in Myanmar, so they have to flee to neighboring countries, such as Indonesia. However, the polemic regarding the issue of the existence of Rohingya refugees in Indonesia still shows that there are differences of opinion between groups who support and oppose it. For this reason, this research aims to determine the dynamics of Indonesian public opinion regarding the Rohingya from 2015-2023 via Twitter, as well as find out the topics that are often discussed each year using LDA. This research compares classification methods using traditional machine learning algorithms (NB, SVM, LR, and DT) and deep learning algorithms (LSTM, GRU, LSTM-GRU, and GRU-LSTM). The research results show that the traditional machine learning algorithm, LR, has the highest accuracy. There has been a change in sentiment from initially being dominated by positive sentiment to negative sentiment which is more dominant in the last five years. The topics that are often discussed for positive sentiment are the support of the Indonesian people for the Rohingya in providing assistance and shelter, while the negative topics are related to concerns about the social, economic, and security impacts that may be caused by the presence of Rohingya refugees.