Pencarian Aturan Asosiasi Semantic Web Untuk Obat Tradisional Indonesia - Ridowati Gunawan; Khabib Mustofa (Jurnal Nasional Teknik Elektro dan Teknologi Informasi, 2016)
Indonesia has more than 2000 types of plants that can be used for medicine. Indonesian traditional medicine called jamu utilizes various of medicinal plants. Since each medicinal plant has different efficacy, jamu also has different efficacy. Jamu can be used to cure certain type of diseases. Jamu that has same efficacy can be produced by many different companies and has different composition. In order to bring benefit for the consumer, knowledge about efficacy of medicinal plants, efficacy of jamu, and composition of jamu is needed. One way to gain knowledge about jamu, along with the entire composition, is to utilize association rule mining technique. If in general the technique only utilizes a single database, in this paper the data source is obtained from semantic web. The data in semantic web is stored in the form of RDF or OWL according to ontology jamu. Data in the form of RDF/OWL is converted into transaction data using library rrdf of R, and its results will be processed using Apriori, which is one of the algorithms in association rule. Results of Apriori algorithm produce association rules on the composition of the jamu along with the value of the support, confidence, and lift ratio. These results indicate the value of lift ratio > 1 which means medicinal plants depend on each other.