Public Sentiment Analysis of KOMINFO Data Leaking by Bjorka using Support Vector Machine

Abstract

An account with the name Bjorka claims to have obtained billions of SIM card registration data in the form of Identity Card and Family Card Nuber from the government database of the Ministry of Communication and Informatics (Kemkominfo), people start questioning the cybersecurity of the government database. The appearance of the Bjorka hacker caused various responses on Twitter, some supported Bjorka’s action and some disagree. Hence the need for sentiment analysis to determine public sentiment is more towards negative or positive, so the government can do evaluation as well as strategic planning to deal with future data leaking incidents. This study uses tweets that contain public responses to predict negative or positive sentiment using Support Vector Machine algorithm. From a total of 1017 public response data, have been found 97.35% (990 tweets) to have negative sentiment and 2.65% (27 tweets) have positive sentiment, so it can be known that public responses are towards negative about data leaking by Bjorka. In conclusion, education to the public about data leaks by Bjorka is not the main priority to do for the government. The government can focus more on dealing with other sectors such as improving the security of the data itself.