FUZZY LOGIC DAN LEXICAL CHAINS UNTUK PERINGKASAN TEKS OTOMATIS

Automatic text summarization (ATS) is a process that was required to produce a summary of a text that contains information with help from a computer. This system is needed to determine the subject matter of a document so that readers can quickly understand. ATS systems need to process the documents resulting in important sentences from the document. In this study, lexical chains were used to generate optimal value for the candidate most powerful word in each sentence. The document is extracted to produce features such as sentence length, the weight of the sentence, the position of the sentence, and the similarity between sentences. The value of the strongest chain will be combined with fuzzy parameters. These features Fuzzy logic predicted the results of a summary of the values of the parameters to be grouped based on the value of linguistic important and unimportant. Furthermore, the final value of the fuzzy will determine the final outcome text summary of the document that was input by the user lexical chains. Testing conducted by manual sentence summary results sourced from respondents and a summary of the results of the ATS system recall, precision and F-measure. Based on the results of research that include the step of determining the problem, the analysis to implementation and testing that has been done before, it can be concluded that the results of the implementation of the method of lexical chains with fuzzy logic for automatic text summarization achieve fairly good