Analysis of Public Perception on Domestic Violence Cases using Support Vector Machine Algorithm - Husnah, Mirdatul; Hidayat, Rahmat (Sistemasi: Jurnal Sistem Informasi, 2025)
Domestic violence is currently a case that is easily exposed by the public. People can easily find many cases through social media. The latest case was experienced by a social media influencer, Cut Intan. This case has attracted public attention and is widely discussed on several social media, one of which is on the X app. With this phenomenon, an analysis of public sentiment towards domestic violence cases that occur in Indonesia is needed. The analysis was conducted using the Support Vector Machine algorithm, a classification algorithm that can classify values into certain classes and has a good level of accuracy. Experiments on analyzing public sentiment towards domestic violence cases using the SVM algorithm resulted in an accuracy score of 95%. The precision score for negative sentiment is 94%, neutral sentiment is 100%, and positive sentiment is 100%. The recall result for negative sentiment is 100%, neutral sentiment is 67%, and positive sentiment has a value of 77%. The results of the f-1 score on negative sentiment are 97%, 80% neutral sentiment, and 87% positive sentiment. While the percentage of community sentiment obtained is 84.40% having negative sentiment, 8.24% having positive sentiment, and 7.36% having neutral sentiment.