Peringkasan Teks Artikel Ilmiah Berbahasa Indonesia dengan Metode Pembobotan Kalimat
Main Article Content
Abstract
Technology of document monitoring is used to save time in digging up important information on documents. Summarize is a process of shrinking text shorter but still retaining the information contained therein. This research discusses the commemoration of the text of journal scientific using sentence weighting methods in the form of TF-IDF and Similarity. The goal the system wants to achieve can be to summarize text by recognizing patterns on text documents in txt format files. The system was built using PHP as a programming language. The trial was conducted using UAT (User Acceptance Testing) to find out the response to the interpreted system, namely by the likers scale questionnaire by dividing 3 aspects of the assessment. From the results of data processing (quantitative) obtained a value of 82.6% for the appearance of the system, a value of 80.2% for the efficiency of sentences generated in the system summary, and a value of 83.7% for satisfaction in using an automatic texting system in scientific articles Indonesian. The results of testing and implementation of the automatic text alerting system are received with a relatively strong acceptance rate.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
References
Nur Hayatin, Chastine Fatichah, Diana Purwitasari, Pembobotan Kalimat BerdasarkanFitur Berita dan Trending Issue Untuk Peringkasan Multidokumen, Malang: Universitas Muhammadiyah Malang, JUTI: Jurnal Ilmiah Teknologi Informasi, Vol 13, No. 1, pp 38-44, 2015.
Putra Edi M, Shaufiah, & Hetti Hidayati, Peringkasan Teks Otomatis dengan Menggunakan Stemming Pada Metode Cenntroid Based (CBS) MultiDokumen Berita, Universitas Telkom: Fakultas Teknik Informatika, 2013.
Trisaputra, Y & Gema Abrianti, Aplikasi Peringkasan Teks Berita Otomatis Menggunakan Pembobotan Kalimat, Bogor: Institut Pertanian Bogor, 2016.
Aristoteles, Pembobotan Fitur Pada Peringkassan Teks Bahasa Indonesia Menggunakan Algoritma Genetika, Bogor:Institut Pertanian Bogor, 2011.
Wahib, A & Winoto, W. A. Menghitung Bobot Sebaran Kata, Malang:Politeknik Kota Malang, Jurnal Buana Informatika, Vol 8 No 1, 2017.
Ardhy, Y.W, Peringkas Teks Otomatis Menggunakan Tanimoto Distance Jaccard Similarity dan Pembobotan Frekuensi Kemunculan Kata untuk Dokumen Berita Berbahasa Indonesia dan Inggris, Malang: Universitas Islam Negeri Maulana Malik Ibrahim Malang, 2015.
Mustaqhfiri, M, Zainal Abidin, & Ririen Kusumawati. Peringkasan Teks Otomatis Berita Berbahasa Indonesia Menggunakan Metode MaximumMargnal Relevance, Malang: Universitas Islam Negri Maulana Malik Ibrahim, 2012.
Sarkar, K, Sentence Clusteringbased Summarization of Multiple Text Documents, International Journal of Computing Science and Communication Technologies, Vol. 2 No.1, pp 413-420, 2009.
Supriatna, Implementasi dan User Acceptance Testing (UAT) terhadap Aplikasi E-Learning Pada Madrasah Aliyah Negri (MAN) 3 Kota Banda Aceh; Banda Aceh: Universitas Negeri Ar-Raniry, 2018.