Automatic Text Summarization Berdasarkan Pendekatan Statistika pada Dokumen Berbahasa Indonesia

  • Christopher Setyawan Teknik Informatika Fakultas Teknik, Universitas Surabaya, Raya Kalirungkut Surabaya-Indonesia 60293
  • Njoto Benarkah Teknik Informatika Fakultas Teknik, Universitas Surabaya, Raya Kalirungkut Surabaya-Indonesia 60293
  • Vincentius Riandaru Prasetyo Teknik Informatika Fakultas Teknik, Universitas Surabaya, Raya Kalirungkut Surabaya-Indonesia 60293
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Abstract

AbstractPropelled by the modern technological innovations data and text will be more abundant throughout the year. With this much text, automatic text summarization is needed now more than ever to help summarize a text. Automatic text summarization is defined as the creation of a shortened version of a text by a computer program, the product of this procedure still contains the most important points of the original text. Statistical approaches is one of automatic text summarization method. There is 5 statistical approaches that being used namely aggregation similarity method, frequency method, location method, title method (if text has a title), dan tf-based query method (if text doesn’t have a title). Cosine similarity is used to calculate title method, aggregation similarity method, and tf- based query method. There is two type of validation, user validation and system validation. For system validation compare the similarity between human summary and summary generated by program, which result in accuracy of 76.7647% for summary with 30% length of the original journal. For user validation result in 82% accuracy. The conclusion based on user validation and system validation is statistical approaches is suitable for automatic text summarization.
Keywords: automatic text summarization, statistical approaches, Indonesian document, cosine similarity

Abstrak— Dengan kemajuan teknologi jumlah data dan teks akan semakin melimpah sepanjang tahun. Dengan banyaknya teks ini dibutuhkan bantuan automatic text summarization untuk merangkum teks tersebut. Automatic text summarization didefinisikan sebagai versi singkat dari suatu teks menggunakan program komputer yang hasilnya masih memiliki informasi penting berupa gagasan dasar dan kata atau kalimat yang dapat merepresentasikan keseluruhan teks original. Salah satu metode dalam automatic text summarization adalah pendekatan statistika. Pendekatan statistika yang digunakan ada 5 yaitu aggregation similarity method, frequency method, location method, title method (bila teks memiliki judul), dan tf-based query method (bila teks tidak memiliki judul). Cosine similarity dipakai untuk perhitungan title method, tf-based query method, dan aggregation similarity method. Validasi dilakukan dengan dua macam validasi. Pertama adalah validasi sistem dengan membandingkan similaritas antara rangkuman program dan rangkuman manusia, yang menghasilkan akurasi 76.7647% untuk rangkuman dengan panjang 30% dari jurnal original. Kedua adalah validasi user yang menghasilkan akurasi 81%. Kesimpulannya berdasarkan validasi user dan validasi sistem yang cukup baik maka pendekatan statistika cocok dipakai dalam kasus automatic text summarization.
Kata kunci: automatic text summarization, pendekatan statistika, cosine similarity, dokumen berbahasa Indonesia

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References


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Published
2021-02-28
How to Cite
Setyawan, C., Benarkah, N., & Prasetyo, V. R. (2021). Automatic Text Summarization Berdasarkan Pendekatan Statistika pada Dokumen Berbahasa Indonesia. KELUWIH: Jurnal Sains Dan Teknologi, 2(1). https://doi.org/10.24123/saintek.v2i1.4045