Peringkasan Teks Ekstraktif Menggunakan Binary Firefly Algorithm

Authors

DOI:

https://doi.org/10.34818/INDOJC.2020.5.2.440

Abstract

Ada banyak informasi teks yang beredar di internet, tetapi manusia sulit mencerna semua informasi tersebut dalam waktu singkat. Peringkasan teks otomatis merupakan teknologi yang membantu seseorang untuk membaca suatu teks secara ringkas dengan menghasilkan ringkasan secara otomatis dari suatu teks tanpa adanya proses penyuntingan manusia terhadap ringkasan tersebut. Pertama, data dari situs diambil menggunakan teknik parsing. Pattern matching juga diperlukan untuk menyaring tag HTML dari data yang diambil sehingga menghasilkan teks murni. Setelah itu, dilanjutkan dengan tokenization untuk memecah teks menjadi kumpulan kata bermakna. Dengan Binary Firefly Algorithm, setiap bagian pada teks diberikan bobot berdasarkan skor kemiripan makna yang terkandung yang ditentukan oleh matriks TF-IDF. Dalam penelitian ini, ringkasan teks dibuat dengan mengambil tujuh bagian teks yang memiliki bobot tertinggi. Ringkasan kemudian dievaluasi menggunakan metrik ROUGE. Hasil penelitian menunjukkan bahwa dibandingkan dengan ringkasan abstraktif, ringkasan ekstraktif memberikan relative improvement sebesar 47,06% pada ROUGE-1, 34,4% pada ROUGE-2, dan 44,92% pada ROUGE-L.

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Author Biographies

Ade Naufal Ammar, Telkom University

Undergraduate student, School of Computing, Telkom University

Suyanto Suyanto, Telkom University

Vice Dean I, School of Computing, Telkom University

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Published

2020-10-02

How to Cite

Ammar, A. N., & Suyanto, S. (2020). Peringkasan Teks Ekstraktif Menggunakan Binary Firefly Algorithm. Indonesian Journal on Computing (Indo-JC), 5(2), 31–42. https://doi.org/10.34818/INDOJC.2020.5.2.440

Issue

Vol. 5 No. 2 (2020): September, 2020

Section

Computer Science

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