SISTEM PERINGKAS TEKS OTOMATIS MULTI DOKUMEN KLIPING ARTIKEL BERITA GEMPA MENGGUNAKAN METODE TF-IDF - Aa Zezen Zaenal Abidin; Enung Nurjanah (Jurnal Teknologi Informasi dan Komunikasi, 2020)
New technology is increasingly evolving so that internet users can find out the news on the internet quickly. Most news stories about the earthquake make it difficult for readers to know the news contents in depth. Because of this, summarizing multi-document texts is important. So that readings are fast and easy and information can be obtained briefly. With the summarization of the text the reader can know the clippings of earthquake news briefly not only from one document but several documents or multiple documents can be done, at least from two documents. The author constructs a prototype multi-document text summarizing system using the term frequency inverse document frequency (TF-IDF) method for breaking the content of documents into sentences, discarding characters, breaking sentences into words, giving weight values to words, adding weight values, measuring idf and TF values -IDF in order to obtain the word weight value of each sentence, t Each document's summary is merged and summarized again, so as to become the third summary as a combination of two documents. Web-based tools are used, the programming language used is PHP and MySQL DBMS. This application can implement multi-document automatic text summarizing news article clippings on the internet TF-IDF method. This system can help find out the important contents of many news article clippings on the internet. the system has the accuracy of the results of the respondent's test 54.45% and the similarity test document accuracy is 78,023%