This paper discusses a summary of Indonesian HSAL detection research, conducted by utilizing the Kitchenham systematic literature review method. Based on our summary, we found that most Indonesian HSAL research still uses the classic machine-learning approach with classic text representation features that experimented on the Twitter text dataset. We also found several challenges and tasks that need to be addressed to build a better HSAL detection system in Indonesian social media that can detect the hate speech target, category, and levels; and the hate speech buzzer, thread starter, and fake account spreader.

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