Generating weighted vector for concepts in indonesian translation of Quran

This paper presents a work in generating Weighted Vector for each Concept in Indonesian Translation of Quran (ITQ). This task is done in aiming to provide a resource needed in implementing a semantic-based question answering system (QAS) for Indonesian ITQ, particularly in retrieving semantically related verses. Semantic approach on QAS employs Ontology concepts of the domain. Since there is no Ontology for ITQ remains, we built one by utilizing the existing Ontology from Quranic Arabic corpus (http://corpus.quran.com/). Furthermore, each leaf concept that enriched by related Quran verse (as its instance) had a representation vector of terms that occur in the corresponding Quran verse to express how strength the concept in relates with verse terms. This vector is assigned with a weight resulted from applying TFIDF method. From 222 leaf concepts in the Ontology, we applied the process only to those that categorized as a member group of Person, Location, and Time named entity. They are 107 in a total. The result shows that the most strength concept in association with verse terms is syaitan which is scored at 0.895 of 1. In overall, 16.82 % concepts had score that more than 0.4, following by 14.95%, 23.36% and 11.21% concepts scored at more than 0.3 ,0.2 and less than 0.1 respectively, and finally the rest ones were the biggest in volume where 33.64% concepts obtained score more than 0.1 and less than 0.2.