Analisa Penggunaan K-Gram pada Karakter, Kata dan Kalimat untuk Mendeteksi Kesamaan Dokumen

Authors

  • Ida Widaningrum Universitas Muhammadiyah Ponorogo
  • Dyah Mustikasari Universitas Muhammadiyah Ponorogo
  • Rizal Arifin Universitas Muhammadiyah Ponorogo
  • Erika Diyah Cahyani Universitas Muhammadiyah Ponorogo

Keywords:

Python, Karakter K-Gram, Kata K-Gram, Kalimat K-Gram, Algoritma Winnowing, Kemiripan Dokumen

Abstract

The use of digital technology is now a necessity; one of its components is documents. Similarity detection can use a variety of methods, including the fingerprinting method. Fingerprint has a working principle using hashing techniques and K-gram. This research is focused on the detection model using Kgram using the winnowing algorithm and python as a programming language. The k-gram parsing test uses 5 k pieces, namely k = 2 k = 3 k = 4 k = 5 k = 6. As a result, the character parsing gets a larger percentage than the manual character percentage. The percentage of word parsing has the closest percentage of the manual percentage. while in sentences, the percentage is the lowest than the manual percentage.

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Author Biographies

Ida Widaningrum, Universitas Muhammadiyah Ponorogo

Department of Informatics Engineering
Faculty of Engineering

Dyah Mustikasari, Universitas Muhammadiyah Ponorogo

Department of Informatics Engineering
Faculty of Engineering

Rizal Arifin, Universitas Muhammadiyah Ponorogo

Department of Informatics Engineering
Faculty of Engineering

Erika Diyah Cahyani, Universitas Muhammadiyah Ponorogo

Department of Informatics Engineering
Faculty of Engineering

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Published

2021-01-01

How to Cite

Widaningrum, I., Mustikasari, D., Arifin, R., & Cahyani, E. D. (2021). Analisa Penggunaan K-Gram pada Karakter, Kata dan Kalimat untuk Mendeteksi Kesamaan Dokumen. Prosiding Seminar Nasional Teknoka, 5, 59–64. Retrieved from https://journal.uhamka.ac.id/index.php/teknoka/article/view/10233