Implementation of JIProlog on an Android-based Song Expert System to Provide Song Recommendations Based on 16 Human Personality Types - Robby Akbar; Taufik Ridwan (Journal of Software Engineering, Information and Communication Technology (SEICT), 2021)
Songs can be enjoyed by someone both in sad and happy heart conditions. The genres of songs are very diverse according to the personality that a person has. Songs also always get attention in society. However, the problem often experienced by some people who rarely enjoy songs is that they don't know what songs suit their personality when they want to listen to music. The purpose of this research is to develop an Android-based Song Expert System application with the implementation of the Java Internet Prolog (JIProlog) library. The method used in designing this expert system is forward chaining; this method aims to browse data on a knowledge base logically. The results of this application will provide song recommendations based on 4 dimensions of personality, namely, dimension 1 (introvert/extrovert), dimension 2 (sensory/intuitive), dimension 3 (thinking/feeling), and dimension 4 (judging/perceiving). Of the 16 human personalities, each personality type will be given 3 song genres. So that users can choose a variety of songs that suit their personality. The test results show that the system successfully displays recommendations with the knowledge base, but the resulting song recommendations still have limitations. Hopefully, this song expert system can help someone get songs that match their personality and the condition of the heart that is being experienced.