<![CDATA[Query Expansion is generally a technique for adding queries in information retrieval in relevance feedback techniques. The initial query will be added with several terms or words in the query to facilitate the process of information retrieval. Information Retrieval begins with the provision of several collections of documents to be used. Using text operations will be processed into an inverted index file. To find it, this research uses TF-IDF weighting method and wordNet based cosine similarity algorithm. By using wordNet, a query is added to correct a particular text so that it matches the concept of a particular sentence. In this research will be used synset in the form of a hyponym word relation to be added to the query. Based on the results of testing using precision @ 20 from 10 queries, the average precision value was 0.7. This means that the probability of the system can rediscover the relevant documents without using the query expansion is 70%. Based on the results of testing using precision @ 20 from 10 queries obtained an average precision value of 0.52. This means that the probability of the system can rediscover the relevant documents without using the query expansion is 52%.]]>
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