The Journal of Enhanced Studies in Informatics and Computer Applications
Vol. 1 No. 1 (2024): JESICA Vol. 1 No. 1 2024

Use Discriminant Analysis to Identify Eroticism-Related Terms in The Lyrics of Dangdut Songs

Herry Wahyu Wibowo (Institut Teknologi, Sains, dan Kesehatan RS.DR. Soepraoen Kesdam V/BRW)
Muhammad Hasbi (Universitas Masamus)
Mochammad Anshori (Institut Teknologi, Sains, dan Kesehatan RS.DR. Soepraoen Kesdam V/BRW)



Article Info

Publish Date
27 Feb 2024

Abstract

The song "Dangdut" is one of the most popular songs in Indonesia, having gained popularity from the 1960s until the present. It's even been acknowledged as authentic Indonesian music. There are both positive and negative effects on the pendengarnya of lagu dangdut. Positive dampening can lower stress levels, and negative dampening occurs when emotions are heightened. If this was brought up by a young child who was not yet fully grown, it would give them a hard time and negatively impact their journey. According to this framework, it is recommended that any eroticism in the lyrics of dance music be identified. It is therefore advised to look for signs of sexuality in the lyrics of dangdut songs. The intention is to restrict and filter the music that kids can listen to. Using LDA and QDA classifiers in conjunction with natural language processing is the suggested approach. According to research findings, LDA can identify more than QDA. The LDA examination yielded the following results: recall = 56.522%, accuracy = 56.522%, precision = 79.13%, and F1score = 65.942%. It has been demonstrated that discriminant analysis, particularly LDA, is useful for classification, as QDA has not shown itself to be the most effective method in this instance.

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Journal Info

Abbrev

jesica

Publisher

Subject

Computer Science & IT

Description

Journal of Enhanced Studies in Informatics and Computer Applications (JESICA) is an international peer-reviewed journal that aims to provide the best analysis and discussion to its readers in the development scope of Data Science, Software Engineering, Computer Applications, Health Informatics, and ...