Klasifikasi Ujaran Kebencian Menggunakan Metode FeedForward Neural Network (IndoBERT)

Abstract

Everyone in Indonesia has freedom of speech, both in real life and on social media. However, freedom of speech carried out without filtering can lead to hate speech. Hate speech is a form of discrimination directed against individuals or groups of individuals based on race, religion, gender, sexual orientation, or other identities. Hate speech can harm other parties which as a result can trigger conflict, violence, and can even cost a person's life. Therefore, it is important to be able to identify and manage this hate speech effectively. One way to manage hate speech on social media is to classify it. In this study, a web-based application was created that can classify a sentence to determine whether the sentence is hate speech or a normal sentence. The model created for classification uses the feedforward neural network method with IndoBERT. Based on the test results, the model created using the feedforward neural network method with IndoBERT provides the best accuracy of 89.52%.