Abstract
This research was conducted to facilitate the interaction between radio broadcasters and radio listeners during the song request process. This research was triggered by the difficulty of the broadcasters in monitoring song requests from listeners. The system is made to accommodate all song requests by listeners. The application produced in this study uses speech emotion recognition technology based on a person's mood obtained from the spoken words. This technology can change the voice into one of the mood categories: neutral, angry, sad, and afraid. The k-Nearest Neighbor method is used to get recommendations for recommended song titles by looking for the closeness of the value between the listener's mood and the availability of song playlists. kNN is used because this method is suitable for user-based collaborative problems. kNN will recommend three songs which then be offered to listeners by broadcasters. Based on tests conducted to the broadcasters and radio listeners, this study has produced a song request application by recommending song titles according to the listener's mood, the text message, the searching songs, and the song requests and the song details that have been requested. Functional test that has been carried out has received 100 because all test components have succeeded as expected.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IJID (International Journal on Informatics for Development)
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
