Peringkasan Teks Ekstraktif Menggunakan Binary Firefly Algorithm

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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
Section
Computer Science