relation: https://digilib.uin-suka.ac.id/id/eprint/13273/
title: ANALISA HASIL PERBANDINGAN PERINGKASAN TEKS OTOMATIS  UNTUK BERITA ONLINE MENGGUNAKAN METODE  TERM FREQUENCY– INVERSE DOCUMENT FREQUENCY  DENGAN CORPUS DAN NON CORPUS  (STUDI KASUS BBC MAGAZINE ONLINE)    
creator: ADITYA DWI PUTRA , NIM. 10651046
subject: Tehnik Informatika
description: Development of Internet technology results the presence of many  websites, including the website of a long article such as magazine online. This  establishment of automatic text summarization expected to help reducing the time  to read the entire contents of the article, so people can speed up read online  magazines without losing the meaning of article  This research begins with the preprocessing 1, including web scraping  process which starts from text downloading from the website server until filtering  text to get the normal text. The next step is pre-processing II, including text  processing whose aim to get the word term. These processes consist of case  folding, sentence splitting, tokenization and filtering stop words. However, if  using the approach without the use of filtering stopwords then there are only  sentence splitting and tokenization process. The results of this processes were then  calculated its weight tf- idf. To generate a summary, the researcher does sentence  extraction process whose high value of tf- idf.  Data testing is using article from the bbc magazine online. Testing is done  in two ways. Firstly, the researcher compares the result of system summary with  the result of manual summary (from abstractor). Secondly, the data testing is  using questionnaires to the respondents to assess the summary result. The results  of the evaluation system that uses filtering corpus generate a summary with  47.50% accuracy (with standard deviation of 6.9 and a range of values between  41.66% to 56.25%). While the results of the evaluation system that does not use  stopwords filtering produces 45.46% accuracy (with standard deviation of 6.2 and  a range of values between 36.84% to 50.00%). Meanwhile, the result of the  second testing using respondents, in general, it can be concluded that produces 4%  of respondents strongly agreed, 72% agreed, 23.2% neutral, 0.8% disagreed, and  stated strongly disagree 0%.    
date: 2014-06-16
type: Thesis
type: NonPeerReviewed
format: text
language: en
identifier: https://digilib.uin-suka.ac.id/id/eprint/13273/1/BAB%20I%2C%20V%2C%20DAFTAR%20PUSTAKA.pdf
format: text
language: en
identifier: https://digilib.uin-suka.ac.id/id/eprint/13273/2/BAB%20II%2C%20III%2C%20IV.pdf
identifier:   ADITYA DWI PUTRA , NIM. 10651046  (2014) ANALISA HASIL PERBANDINGAN PERINGKASAN TEKS OTOMATIS UNTUK BERITA ONLINE MENGGUNAKAN METODE TERM FREQUENCY– INVERSE DOCUMENT FREQUENCY DENGAN CORPUS DAN NON CORPUS (STUDI KASUS BBC MAGAZINE ONLINE).  Skripsi thesis, UIN SUNAN KALIJAGA.