| Summary: | 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.
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