4 research outputs found

    Plagiarism detection for Indonesian texts

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    As plagiarism becomes an increasing concern for Indonesian universities and research centers, the need of using automatic plagiarism checker is becoming more real. However, researches on Plagiarism Detection Systems (PDS) in Indonesian documents have not been well developed, since most of them deal with detecting duplicate or near-duplicate documents, have not addressed the problem of retrieving source documents, or show tendency to measure document similarity globally. Therefore, systems resulted from these researches are incapable of referring to exact locations of ``similar passage'' pairs. Besides, there has been no public and standard corpora available to evaluate PDS in Indonesian texts. To address the weaknesses of former researches, this thesis develops a plagiarism detection system which executes various methods of plagiarism detection stages in a workflow system. In retrieval stage, a novel document feature coined as phraseword is introduced and executed along with word unigram and character n-grams to address the problem of retrieving source documents, whose contents are copied partially or obfuscated in a suspicious document. The detection stage, which exploits a two-step paragraph-based comparison, is aimed to address the problems of detecting and locating source-obfuscated passage pairs. The seeds for matching source-obfuscated passage pairs are based on locally-weighted significant terms to capture paraphrased and summarized passages. In addition to this system, an evaluation corpus was created through simulation by human writers, and by algorithmic random generation. Using this corpus, the performance evaluation of the proposed methods was performed in three scenarios. On the first scenario which evaluated source retrieval performance, some methods using phraseword and token features were able to achieve the optimum recall rate 1. On the second scenario which evaluated detection performance, our system was compared to Alvi's algorithm and evaluated in 4 levels of measures: character, passage, document, and cases. The experiment results showed that methods resulted from using token as seeds have higher scores than Alvi's algorithm in all 4 levels of measures both in artificial and simulated plagiarism cases. In case detection, our systems outperform Alvi's algorithm in recognizing copied, shaked, and paraphrased passages. However, Alvi's recognition rate on summarized passage is insignificantly higher than our system. The same tendency of experiment results were demonstrated on the third experiment scenario, only the precision rates of Alvi's algorithm in character and paragraph levels are higher than our system. The higher Plagdet scores produced by some methods in our system than Alvi's scores show that this study has fulfilled its objective in implementing a competitive state-of-the-art algorithm for detecting plagiarism in Indonesian texts. Being run at our test document corpus, Alvi's highest scores of recall, precision, Plagdet, and detection rate on no-plagiarism cases correspond to its scores when it was tested on PAN'14 corpus. Thus, this study has contributed in creating a standard evaluation corpus for assessing PDS for Indonesian documents. Besides, this study contributes in a source retrieval algorithm which introduces phrasewords as document features, and a paragraph-based text alignment algorithm which relies on two different strategies. One of them is to apply local-word weighting used in text summarization field to select seeds for both discriminating paragraph pair candidates and matching process. The proposed detection algorithm results in almost no multiple detection. This contributes to the strength of this algorithm

    Plagiarism detection for Indonesian texts

    Get PDF
    As plagiarism becomes an increasing concern for Indonesian universities and research centers, the need of using automatic plagiarism checker is becoming more real. However, researches on Plagiarism Detection Systems (PDS) in Indonesian documents have not been well developed, since most of them deal with detecting duplicate or near-duplicate documents, have not addressed the problem of retrieving source documents, or show tendency to measure document similarity globally. Therefore, systems resulted from these researches are incapable of referring to exact locations of ``similar passage'' pairs. Besides, there has been no public and standard corpora available to evaluate PDS in Indonesian texts. To address the weaknesses of former researches, this thesis develops a plagiarism detection system which executes various methods of plagiarism detection stages in a workflow system. In retrieval stage, a novel document feature coined as phraseword is introduced and executed along with word unigram and character n-grams to address the problem of retrieving source documents, whose contents are copied partially or obfuscated in a suspicious document. The detection stage, which exploits a two-step paragraph-based comparison, is aimed to address the problems of detecting and locating source-obfuscated passage pairs. The seeds for matching source-obfuscated passage pairs are based on locally-weighted significant terms to capture paraphrased and summarized passages. In addition to this system, an evaluation corpus was created through simulation by human writers, and by algorithmic random generation. Using this corpus, the performance evaluation of the proposed methods was performed in three scenarios. On the first scenario which evaluated source retrieval performance, some methods using phraseword and token features were able to achieve the optimum recall rate 1. On the second scenario which evaluated detection performance, our system was compared to Alvi's algorithm and evaluated in 4 levels of measures: character, passage, document, and cases. The experiment results showed that methods resulted from using token as seeds have higher scores than Alvi's algorithm in all 4 levels of measures both in artificial and simulated plagiarism cases. In case detection, our systems outperform Alvi's algorithm in recognizing copied, shaked, and paraphrased passages. However, Alvi's recognition rate on summarized passage is insignificantly higher than our system. The same tendency of experiment results were demonstrated on the third experiment scenario, only the precision rates of Alvi's algorithm in character and paragraph levels are higher than our system. The higher Plagdet scores produced by some methods in our system than Alvi's scores show that this study has fulfilled its objective in implementing a competitive state-of-the-art algorithm for detecting plagiarism in Indonesian texts. Being run at our test document corpus, Alvi's highest scores of recall, precision, Plagdet, and detection rate on no-plagiarism cases correspond to its scores when it was tested on PAN'14 corpus. Thus, this study has contributed in creating a standard evaluation corpus for assessing PDS for Indonesian documents. Besides, this study contributes in a source retrieval algorithm which introduces phrasewords as document features, and a paragraph-based text alignment algorithm which relies on two different strategies. One of them is to apply local-word weighting used in text summarization field to select seeds for both discriminating paragraph pair candidates and matching process. The proposed detection algorithm results in almost no multiple detection. This contributes to the strength of this algorithm

    Penerapan Simhash dan Hamming distance dalam Deteksi kemiripan Teks Berita

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    Daur Ulang Text didefinisikan sebagai pemanfaatan sumber tulisan yang ada untuk penulisan sebuah teks baru. Persentase penggunaan ulang teks dari sumber sebelumnya sangatlah bervariasi.  Jika prosentase penggunaan tersebut tinggi dan berasal dari sebuah sumber, maka teks yang baru menjadi teks duplikat atau hampir duplikat dengan teks sumbernya. Meskipun beberapa genre teks bisa diterima, keberadaan teks duplikat dan hampir dupilkat ini menyebabkan ketidak-efisienan penyimpanan dan pencarian. Untuk itu diperlukan sebuah system deteksi kemiripan teks yang akan mengidentifikasi teks mana saja yang dupilkat dan hampir duplikat. Untuk itu, penelitian ini berfokus pada deteksi kemiripan teks dengan mengaplikasikan algoritma Simhash. Algoritma ini digunakan untuk menghasilkan fingerprint dokumen yang berfungsi sebagai fitur dokumen yang digunakan sebagai dasar pembanding tingkat kemiripan teks. Kemiripan sebuah teks terhadap teks lainnya diukur dengan menggunakan jarak Hamming. Dalam ekperimen yang difokuskan pada dokumen duplikat dan hampir duplikat, tingkat Recall dokumen cukup tinggi yakni 80%. Ini berarti bahwa sistem yang dikembangkan mampu menemenukan pasangan dokumen duplikat dengan baik. &nbsp

    ANALISIS KUALITAS LAYANAN SISTEM INORMASI SIMPEL DENGAN METODE IMPORTANCE PERFORMANCE ANALYSIS (IPA)

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    Dinas Penanaman Modal Terpadu Satu Pintu (DPMPTSP) Provinsi Riau memiliki layanan Sistem Informasi pelayanan (SIMPEL) yang memiliki tujuan untuk memudahkan pengguna dalam kepengurusan surat perizinan riset dan pra riset. Namun, setelah dilakukan wawancara oleh pihak pelayanan riset dan pra riset terdapat permasalahan yang sering diadukan oleh pengguna seperti Pemohon kurang mengerti terkait prosedur pembuatan surat izin secara online, kesalahan pada berkas sering sekali dilakukan oleh pemohon, surat izin penelitian diterbitkan butuh waktu lebih dari 1 minggu, tidak adanya prosedur terkhusus terhadap pelayanan perizinan penelitian, tidak disediakannya opsi pilihan bahasa dalam penggunaan website, yakni bahasa Indonesia atau bahasa Inggris. Dengan adanya permasalahan tersebut maka dilakukan sebuah penelitian menggunakan e�govqual dan IPA. Variabel dari e-govqual digunakan sebagai alat ukur kualitas layanan sesuai persepsi pengguna. Setelah dilakukan perhitungan terhadap kuesioner yang telah didapat hasilnya adalah <100% yaitu 79,79% artinya layanan Simpel dinilai belum me menuhi harapan pengguna. Kata Kunci: E-Govqual, IPA, Riset dan Pra riset, Simpel
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