<![CDATA[Listening to music has become a hobby for everyone. Listening music does have its own charm, with a lot of genres out there, we can listen music anytime and anywhere we want. Also, with a lot of types of music too, we can match with the situation of the user. This can be a problem for music listeners who want a specific music for their taste. Example when somebody having a bad day, they tend to have a bad mood. This problem can be solved by listening to music with a slow rhythm. With problem something like this, we can make system recommendation based on user context. The Development of Application Recommendation Based on Mood User is to make android application with emotion based and using expert system method with the forward chaining method. For recommendation, playlist provided by system is derived from experts. Functional testing of the system, resulting in a valid outcome with a value of 100%. For usability testing, we are using the System Usability Scale with a value of 84. Which is categorized as excellent. Lastly, for accuracy testing, we are comparing using system output and what expert recommended as result with an accuracy value of 80%.]]>
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