Penerapan Algoritma Text Mining dan Lexrank dalam Meringkas Teks Secara Otomatis
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Ahmad Fauzi
*
Universitas Budi Darma, Medan,
Indonesia
(*) Corresponding Author
Abstract
The growth of media and online news has allowed writers to automate research in the field of text summarization. News that offers a quick and concise concept, but in reality digital news is not organized and it takes so long to find the essence of the news. Document summarization is an effective way to get information from a document without reading the entire document. However, document summaries for Indonesian are still relatively small compared to other languages. This study develops document summarization automatically using a graph-based method, namely the Lexrank Algorithm which can be proven by research that has been tested using Indonesian news data obtained from liputan6.com. The number of sentences extracted is 25%-50% of the total sentences in the document. The results of the Lexrank summary in order of the highest weight order are = D2 = 1,433, D10 = 1,289, D3 = 1,253, ….. D8 = 0.673. The largest value from the summary will be arranged according to the order of words so as to get the summary of the news.
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