Detecting Hate Speech on Indonesian Twitter Using Logistic Regression

Hate speech on social media has become a significant issue, particularly due to the diverse nature of these platforms where people from around the world interact. Social media, intended as a place for communication and connection, has unfortunately also become a place for expressing hate towards individuals or groups. Numerous studies have been conducted to understand and address this problem. These hateful messages can target people based on their race, religion, ethnicity, sexual orientation, disability, or any other factor that can be used to divide. This particular research focuses on detecting hate speech on Indonesian Twitter. The methodology involves several steps: Data collection, data preparation, data analysis, validation and testing, evaluation. By implementing Natural Language Processing techniques for Logistic Regression, this study aims to contribute valuable insights for future research on hate speech detection especially within Indonesian social media. The expected outcome is to enhance the understanding and detection of hate speech, thereby helping to create a safer and more inclusive online environment.