SESS: Utilization of SPIN for Ethnomedicine Semantic Search

Indonesia has biodiversity which is very beneficial for human life. Existing applications for ethnomedicine have been developed using conventional methods that only utilized SPARQL Protocol and RDF Query Language (SPARQL), so they still have limitations in representing knowledge and its retrieval. Those conventional methods are which based of relational database and ontology that has not utilized inference in its query process. Therefore, this work proposed SPIN for Enthnomedicine Semantic Search (SESS), a framework of the semantic search for medicinal plants that were developed by using SPIN (SPARQL Inferencing Notation). SESS has two main parts, the ontology design included SPARQL Inferencing Notation (SPIN) library and query process. The experiments were assessed in terms of execution time, query variation and accuracy. The obtained results showed a ratio of precision at 1, recall at 0.98 and the average value of the f-measure was 0.99. Utilizing SPIN also decrease the time consuming to obtain the result by around .