The Comparation of Distance-Based Similarity Measure to Detection of Plagiarism in Indonesian Text

Plagiarism is the act of copying the work of another person in the form of writing, ideas, creative ideas or other without including the source of the work or idea. This action is of course very disrespectful, violates the code of ethics and is opposed by all parties, both by scientists and the government. This happens because the use of the internet provides unlimited information services. Many studies have been carried out, raising the theme of this plagiarism. This article will review how far the plagiarism research has been done on Indonesian writing. By knowing the development of plagiarism research, further research will have better sustainability.

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“…The similarity measure is also compared [49]. This is performed along with the Rabin-Karp algorithm using Indonesian texts.…”

Section: Discussion and Results Indonesian Language Plagiarism Detectionmentioning

confidence: 99%

A review of detection plagiarism in indonesian language

Widaningrum¹,

Mustikasari²,

Arifin³

et al. 2018

IJARLIT

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“…Dice Coefficient Similarity merupakan metode pengukuran yang paling umum digunakan untuk menghitung nilai kesamaan dengan pendekatan K-Gram [9].…”

Section: E Dice Coefficient Similarityunclassified

Implementasi Algoritma Rabin-Karp untuk Pendeteksi Plagiarisme pada Dokumen Tugas Mahasiswa

Filcha¹,

Hayaty

2019

Juita

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1 asvarizal.filcha@students.amikom.ac.id 2 mardhiya_hayati@amikom.ac.idAbstrak-Perkembangan pada dunia teknologi informasi mengakibatkan perguruan tinggi mengurangi penggunaan kertas sehingga banyak tugas mahasiswa yang dikumpulkan dalam bentuk digital. Penggunaan digital menyebabkan semakin mudahnya mahasiswa untuk melakukan plagiarisme. Sehingga diperlukan sebuah sistem untuk melakukan pemeriksaan plagiarisme pada dokumen tugas antar mahasiswa dengan cepat dan tepat. Metode yang dapat digunakan adalah menggunakan algoritma Rabin-Karp. Algoritma Rabin-Karp memiliki keunggulan pencarian string dengan pola yang panjang. Algoritma Rabin-karp dalam sistem ini memiliki langkah -langkah text preprocessing yang terdiri case folding, tokenizing, punctuation removal, stopword removal dan stemming. Hasil dari text preprocessing inilah yang akan di proses menggunakan algoritma Rabin-karp. Hasil dari metode ini adalah nilai kemiripan dari tugastugas mahasiswa yang dihitung menggunakan dice coefficient. Perhitungan akurasi dengan melakukan 20 perbandingan antara sistem pendeteksi plagiarisme dan software Plagiarisme Checker X menggunakan confusion matrix menghasilkan tingkat keakuratan sebesar 90%. Kata Kunci -Rabin-Karp,plagiarisme, text preprocessing, dice coefficient. Abstract-The Information and technology development causes universities reduce paper usage so that the student's assignments can be collected in digital form. The digital form usage causes students can easily plagiarism the assignments. So, it is needed a system to check the plagiarism on assignment documents among students quickly and accurate. The method that can be used is Rabin-Karp algorithm. Rabin-Karp algorithm has excellence in searching strings with long pattern. Rabin-Karp algorithm in this system has text preprocessing steps that consist of case folding, tokenizing, punctuation removal, stopword removal and stemming. The result from the text preprocessing will be processed using Rabin-Karp algorithm. The outcome of this method is the similiarity percentage of student's assignments calculated using dice coefficient. The accuracy calculation by doing 20 comparisons between plagiarism checker system andPlagiarism Checker X software using confusion matrix is 90%.

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“…Tree edit distance was introduced in computing the text similarity between the syntactic n-grams and vector space model [16]. Several distance based similarity measures such as Dice's similarity coefficient, Cosine similarity, and Jaccard coefficient was compared using document fingerprint and it is proved that the cosine similarity provides the better result for Indonesian text [17]. These methods lack in fast processing.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Technique Using Multiple K-Shingling Based Weighted Dissimilarity Score for Web Content Outlier Mining

Khan¹,

Ahmed²,

Almistarihi³

2019

IJIES

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The technological evolution of Internet and Web along with several applications leads to the problem of redundancy as the documents are unanimously forwarded and are stored in several servers and platforms. Recently, not only duplicate documents but also near-duplicate documents affect the performance of the search results. The main objective of this paper is to provide significant documents by eliminating the redundancy and near redundancy documents present in the web search results. The proposed model comprises of two phases such as pre-processing phase and dissimilarity computation phase. For dissimilarity computation, the proposed model employs multiple kshingling based dissimilarity score to identify the duplicate and near-duplicate documents which are considered as the outliers present in the set of input web documents. The proposed model has been evaluated using several experimental analysis. As there are no real datasets available for duplicate detection, datasets have been created and the performance evaluation is carried out with the created datasets. Several statistical analysis has been made wherein the average specificity, sensitivity, precision, and accuracy are 87%, 93%, 80%, and 92% respectively. The comparative analysis has also been made with various existing methods, in which the proposed model provides better results than existing methods in removing near-duplicates. The proposed multiple k-shingling based weighted dissimilarity model effectively detects the duplicates and near-duplicates when the number of outliers is minimum.

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The Comparation of Distance-Based Similarity Measure to Detection of Plagiarism in Indonesian Text

Cited by 8 publications

References 4 publications

A review of detection plagiarism in indonesian language

A review of detection plagiarism in indonesian language

Implementasi Algoritma Rabin-Karp untuk Pendeteksi Plagiarisme pada Dokumen Tugas Mahasiswa

A Novel Technique Using Multiple K-Shingling Based Weighted Dissimilarity Score for Web Content Outlier Mining

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