SISTEM QUESTION ANSWERING FIQIH BERBASIS ONTOLOGI DENGAN KLASIFIKASI PERTANYAAN MENGGUNAKAN SUPPORT VECTOR MACHINE - SIAMI, M. IKBAL ([Yogyakarta] : Universitas Gadjah Mada, 2015)
People are more likely to ask the expert (chaplain) through the internet rather than reading classic book. meanwhile, the expert available is limited. In this condition, we needed a system that could be provide answers automatically. Question Answering (QA) system is necessary that can provide answers automatically, precise and concise. This research was proposed a machine learning approach and ontology to build a QA system of fiqih issues. Support Vector Machine (SVM) is used in machine learning algorithms. Components of the system is divided into several sub-components, namely processors question, classification questions and answers processors. SVM algorithm is part of the questions classification component which aimed to determine the type of question. Ontology is used because of its ability in the process of semantic analysis. Semantic analysis is used to obtain content targets of the user's question. Types of questions is proposed into 4 types: dalil, deskripsi, hukum, and definisi. The combination of types and content targets is generated a question focus, so the answer is presented based on the focus of the question that has been obtained. Based on test results, QA system of fiqh has the ability to detect an irrelevant question, determine the type of questions well, and is able to perform semantic analysis. So that the system can provide the correct answer achived 86.71% accuracy.