Aplikasi Pendeteksi Tingkat Kesamaan Dokumen Teks: Algoritma Rabin Karp Vs. Winnowing

Cited by 7 publications

(10 citation statements)

References 7 publications

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“…The resulting accuracy results are higher if you use an English-Indonesian dictionary than if you don't use an English-Indonesian dictionary 3 [7] There are acts of plagiarism against other people's work freely via the internet…”

Section: Winnowingmentioning

confidence: 99%

“…The hash value is a numeric value obtained from ASCII calculations [6]. The accuracy results of the Winnowing method are better than the rabin carp method, which produces an accuracy rate of 88.89% and a processing time of 0.13 seconds, while the rabin carp method produces an accuracy rate of 37.50% with a processing time of 0.19 seconds [7]. Several previous research groups discussing the same subject with the title can be seen in Table 1 The occurrence of acts of plagiarism in writing essays…”

Section: Introductionmentioning

confidence: 99%

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Cross-Language Text Document Plagiarism Detection System Using Winnowing Method

Mentari

Rozi

Rahayu³

2022

JAIS

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Currently, there are many text documents such as journals scattered on the internet, both Indonesian and English-language journals. With this, it is possible to act plagiarism by copying from foreign journals that are translated into other languages or copying directly without being changed from the original language. One way that can suppress these actions is to build a plagiarism detection system for cross-language text documents. The method that can be used to detect document plagiarism is the Winnowing method. Winnowing method is a method where text input will be processed to produce a hash value called a fingerprint. This study aims to build a system that can detect plagiarism of text documents in different languages using the Winnowing method. Text documents that can be tested are input text and PDF files. Documents used in system testing are journals that have the same topic. The results of the highest level of accuracy produced between the calculation of the Jaccard Coefficient with the Plagiarism Checker X application are in the fourth scenario with an average percentage value of 84.7%.

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Section: Winnowingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cross-Language Text Document Plagiarism Detection System Using Winnowing Method

Mentari

Rozi

Rahayu³

2022

JAIS

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“…Berdasarkan penelitian terdahulu menyatakan bahwa Algoritma Winnowing mendapatkan hasil terbaik pada uji coba dengan nilai n-gram (n) = 3 dan window (w) = 3, sehingga dapat disimpulkan Algoritma Winnowing memiliki persentase akurasi yang baik [4] [5]. Pada penelitian perbandingan antara algoritma Rabin-Karp dengan Algoritma Winnowing lebih unggul dibandingkan dengan Algoritma Rabin-Karp dari kedua variabel yang menjadi landasan perbandingan karena bukan hanya nilai hash saja yang dibandingkan, namun nilai hash yang ada akan dikonversikan terlebih dulu kedalam window baru sehingga dapat diketahui nilai hash yang sama [6]…”

Section: Jurnal Sistem Informasi Dan Telematika (Telekomunikasi Multi...unclassified

Analisis Kinerja Algoritma Winnowing pada Pendeteksian Plagiarisme

Saputra

Erlangga

Tanjung

2022

Explore. jurnal. sistem. inf. dan. telematika

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The problem of plagiarism at this time can be solved. This research was carried out by analyzing the performance of the Winnowing Algorithm on plagiarism detection. The choice of the Winnowing Algorithm is because by calculating the hash value of k-grams, the rolling hash function is used to find the hash value, after which a window is formed from the hash value. In each window, the smallest hash value is selected. When more than one hash has the lowest value, the rightmost hash value is selected. Then all selected hash values are stored to be used as document fingerprints. This fingerprint serves as a basis for comparing the similarity of embedded text. The results of the Winnowing Algorithm performance analysis research show that this algorithm is quite good at detecting text similarity or plagiarism with the result of the smallest percentage value of 10 tests shown in the 10th test with n-gram values n = 10, window w = 3, time process sec = 0.0094 with a result of 47% text similarity. This result is better than the results of the similarity of the Rabin Karp Algorithm from the results of previous studies.

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“…Pencarian data di komputer, baik itu secara online ataupun offline telah berkembang banyak metode yang semakin menyempurnakan hasil pencarian. Hal ini juga meningkatkan kepuasan end user dalam mencari informasi [1]. Para pakar kecerdasan buatan semakin meningkatkan cara kerja pencarian dokumen dengan algoritma dan metode yang mendekati alamiah pikiran manusia [2] [3].…”

Section: Pendahuluanunclassified

“…Aljabar boole merumuskan beberapa operator matematika antara AND, OR, NOT, NOT AND dan NOT OR [4] [5]. Jika mesin pencari menemukan kesesuaian dokumen sesuai dengan kata kunci maka langsung ditampilkan sebagai hasil temuan [1].…”

Section: Pendahuluanunclassified

Perbandingan Boolean Model Dan Vector Space Model Dalam Pencarian Dokumen Teks

Susanti¹,

Azmi²,

Ali³

et al. 2020

Digitalzone

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Perkembangan teknologi informasi di era globalisasi saat ini, membuat semua aspek kehidupan kita berubah dan tidak dapat dihindarkan dari pengaruh kemajuan zaman. Untuk mendapatkan data dan informasi yang kita inginkan bukanlah perkara mudah, mengingat sedemikian banyaknya informasi yang tersedia untuk berbagai keperluan dengan berbagai gaya penyajian. Pencarian data di komputer, baik itu secara online ataupun offline berkembang banyak metode yang semakin menyempurnakan hasil pencarian. Hal ini juga meningkatkan kepuasan pengguna dalam mencari informasi. Metode yang umum digunakan dalam melakukan pencarian adalah Boolean Model. Metode lainnya adalah Vector Space Model (VSM). VSM yaitu model yang digunakan untuk mengukur kueri antara suatu dokumen dengan suatu kata kunci. Oleh karena itu, penulis bertujuan untuk membandingkan kedua metode tersebut dari kecepatan (waktu) pencarian dan jumlah temuan. Kecepatan tersebut dihitung berdasarkan lama waktu pencarian untuk kedua metode tersebut. Hasil yang didapati adalah perbandingan waktu pencarian antara boolean model dan vector space model didapati bahwa boolean model lebih cepat dengan selisih 30 sampai 50 detik. Perbandingan untuk hasil temuan didapati bahwa vector space model mempunyai hasil temuan yang sama dengan boolean model yang menggunakan operator or, sedangkan dengan operator and dan gabungan and serta or didapati bahwa jumlah hasil temuan tidak sama dengan vector space model. Kata kunci: Perbandingan, Boolean Model, Vector Space Model, Pencarian, Dokumen Teks Abstract The development of information technology in the current era of globalization, makes all aspects of our lives change and cannot be avoided from the influence of the times. To get the data and information that we want is not an easy matter, considering that so much information is available for various purposes with various styles of presentation. Searching data on a computer, be it online or offline, there are many methods that improve the search results. It also increases user satisfaction in finding information. The most commonly method of searching is the Boolean Model. Another method is the Vector Space Model (VSM). VSM is a model used to measure queries between a document and a keyword. Therefore, the authors aim to compare the two methods from the speed (time) of the search and the number of findings. The speed is calculated based on the search time for both methods. The result is that the comparison between boolean model and vector space model shows that the boolean model is faster by a difference of 30 - 50 seconds. The comparison for the foundings document text shows that vector space model has the same findings as the boolean model using the or operator, whereas with the and operator and the combination of operator and or it is found that the number of findings is not the same as vector space model. Keywords: Comparison, Boolean Model, Vector Space Model, Search, Text Documents

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Aplikasi Pendeteksi Tingkat Kesamaan Dokumen Teks: Algoritma Rabin Karp Vs. Winnowing

Cited by 7 publications

References 7 publications

Cross-Language Text Document Plagiarism Detection System Using Winnowing Method

Cross-Language Text Document Plagiarism Detection System Using Winnowing Method

Analisis Kinerja Algoritma Winnowing pada Pendeteksian Plagiarisme

Perbandingan Boolean Model Dan Vector Space Model Dalam Pencarian Dokumen Teks

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