A Systematic Overview of Fuzzy Extended Entity Relationship (Fuzzy EER) Model Using Practical Examples

Most real-world data are vague and imprecise, so traditional relational databases cannot represent, integrate, and manage them effectively. In this research, we gave an overview of the application of fuzzy logic to the conceptual modeling facet of database design, which is an enhancement of the Extended Entity Relationship (EER) model. This is done to give a clearer picture of how imprecise and vague data are represented and managed, especially in multiple-criteria decision-making database systems. To achieve this, an overview of fuzzy attributes, fuzzy values in the attributes, notation for fuzzy representations, fuzzy degree in each value of an attribute, fuzzy degree in a set of values of different attributes, fuzzy degree with its own meaning and fuzzy degree to the model was carried out with practical examples.