Analisis Sentimen Inses di Social Media menggunakan Algoritma Naïve Bayes

Tasya Salsabilla; Debby Alita

doi:10.30591/jpit.v9i3.6611

Analisis Sentimen Inses di Social Media menggunakan Algoritma Naïve Bayes

Tasya Salsabilla, Debby Alita

Abstract

Sexual violence, especially against women and children, is a serious problem in Indonesia. Cases are increasing every year, including incest, which involves sexual relations between close family members. Girls, who are often considered weak and vulnerable, are the main victims. The latest data from the National Commission on Violence Against Women records a decrease in incest cases from 1,210 in 2017 to 215 in 2020. However, attention is still needed, especially because biological fathers are the largest perpetrators. This research uses the Naïve Bayes algorithm for sentiment analysis. This algorithm is an effective classification method based on Bayes' theorem with simple assumptions but is quite effective. Assuming that each feature in the data is independent, Naïve Bayes can work well in text analysis. The research results showed an accuracy rate of 94%. Continued attention to sexual violence, especially incest, is needed to protect vulnerable girls. Protection efforts must continue to be improved, including the application of sentiment analysis methods such as Naïve Bayes for monitoring and early detection. Public awareness and cross-sector cooperation are also key in overcoming this phenomenon.

Keywords

Kekerasan Seksual, Inses, Algoritma Naïve Bayes, Analisis Sentimen.

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DOI: https://doi.org/10.30591/jpit.v9i3.6611