Framework With An Approach To The User As An Evaluation For The Recommender Systems

This research is a framework with an approach to the user as an evaluation for the recommendation system. Prediction algorithm can provide accuracy to the recommendation system. The recommendation system strongly influences user experience in the recommendation system. The relationship between objective system aspects and user behavior is carried out with a framework based on a collection of perceptions and evaluations with various aspects of subjective experience through personal and situational characteristics of user experiences. This research is also supported by related literature in mapping the framework. In this way, the framework can be validated. Analysis of Field trials and experiments with structural equation modeling. The results showed that the subjective system aspects and user experience could provide an explanation of why and how the user experience emerges from the recommendation system. Perceived quality and variation of recommendations are important mediators in predicting objective system aspects of user experience components such as perceived processes or difficulties, systems in the form of perceived system effectiveness, results in the form of choice of satisfaction. This study also found that there was a correlation of behavior from subjective aspects such as a lack of search results, this shows the results of the effectiveness of the system. There is a relationship between aspects of the system with personal and situational characteristics indicated by the number of feedback preferences from users in exchange for system usability and user privacy.