Indonesian medical retrieval case based on knowledge association rule similarity

In Case Based Reasoning (CBR), retrieval phase is one of the important phases in view of the dependence of the overall effectiveness of the CBR system on the case retrieval stage. To run the process of finding a new case, CBR systems typically utilize knowledge similarity called Similarity-Based Reasoning (SBR) in which the knowledge encoded in the form of term measures is used to calculate the similarity between a new case with the old one. In this paper, we attempt to build a new concept of similarity text for retrieval case on Indonesian medical sentences. The method to be used is the knowledge base of similarity in which the stage included: (i) the utilization of the knowledge for decision-case association, and (ii) the association extraction of knowledge by creating a rule based on attribute data to generate a subset of cases and solutions in a number of cases. The test results then showed the highest values found in the case of the active sentence form at 88.18% for precision, 88.23% for recall and 89.12% for F1-Measure.