Abstract
Opinions are always expressed in comments or reviews. An automated opinion mining system has been seen as one of the desirable intelligence business tools. The system can extract public opinion about a certain topic, product or service which is embedded in unstructured texts. Extracting opinions from reviews and comments requires a system to deal with natural language texts. The current approach in opinion mining is classifying sentiment words into two polar; positive and negative. Unfortunately, this is not enough. Words such as "excellent" and "good" are both classified into positive, however, the positive degree of both words are not the same. This paper introduces the use of a fuzzy lexicon and fuzzy sets in deciding the degree of positive and negative. Our experimental result shows that the approach is able to extract opinions and present the opinions in a more efficient way.