A review of detection plagiarism in indonesian language

Ida Widaningrum(1*), Dyah Mustikasari(2), Rizal Arifin(3), Sugianti Sugianti(4),

(1) Universitas Muhammadiyah Ponorogo
(2) Universitas Muhammadiyah Ponorogo
(3) Universitas Muhammadiyah Ponorogo
(4) Universitas Muhammadiyah Ponorogo
(*) Corresponding Author

Abstract


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.

Keywords


plagiarism; creative ideas or ideas; Indonesian

Full Text:

PDF

References


Pemerintah Republik Indonesia, “Undang-Undang Republik Indonesia Nomor 19 Tahun 2002 Tentang Hak Cipta,” 2002.

Pemerintah Republik Indonesia, “Undang-Undang Republik Indonesia Nomor 20 Tahun 2003 Tentang Sistem Pendidikan Nasional,” Dep. Pendidik. Nas., pp. 1–33, 2003.

Kementerian Pendidikan Nasional Indonesia, “Peraturan Menteri Pendidikan Nasional Republik Indonesia tentang Pencegahan dan Penanggulangan Plagiat di Perguruan Tinggi Nomor 17 Tahun 2010.” 2010.

Http://www.kbbionline.com/arti/kbbi, “Kamus Besar Bahasa Indonesia Online,” diakses tgl 26 September 2018, 2018. .

Https://kbbi.kemdikbud.go.id, “Kamus Besar Bahasa Indonesia Online,” diakses tanggal 26 September 2018. .

Https://www.merriam-webster.com/dictionary, “merriam-webster dictinary online,” diakses tanggal 26 Sept. 2018.

A. M. E. T. Ali, H. M. D. Abdulla, and V. Snasel, “Survey of Plagiarism Detection Methods,” 2011 Fifth Asia Model. Symp., pp. 39–42, 2011.

S. M. Alzahrani, N. Salim, and A. Abraham, “Understanding plagiarism linguistic patterns, textual features, and detection methods,” IEEE Trans. Syst. Man Cybern. Part C Appl. Rev., vol. 42, no. 2, pp. 133–149, 2012.

H. A. Chowdhury and D. K. Bhattacharyya, “Plagiarism: Taxonomy, Tools and Detection Techniques,” 19th Natl. Conv. Knowledge, Libr. Inf. Netw. (NACLIN 2016), no. 1, 2016.

S. A. Hiremath and M. S. Otari, “Plagiarism Detection-Different Methods and Their Analysis: Review,” Int. J. Innov. Res. Adv. Eng., vol. 1, no. 7, pp. 2349–2163, 2014.

A. S. Hamza Osman Naomie; Abuobieda, Albaraa, “Survey of Text Plagiarism Detection,” Comput. Eng. Appl. J., vol. 1, no. Vol 1, No 1: June 2012, pp. 37–45, 2012.

C. Grozea, C. Gehl, and M. Popescu, “ENCOPLOT: Pairwise sequence matching in linear time applied to plagiarism detection,” CEUR Workshop Proc., vol. 502, pp. 10–18, 2009.

C. Basile, D. Benedetto, E. Caglioti, G. Cristadoro, and M. D. Esposti, “A plagiarism detection procedure in three steps: Selection, matches and squares,” CEUR Workshop Proc., vol. 502, pp. 19–23, 2009.

A. Barrón-Cedeño and P. Rosso, “On automatic plagiarism detection based on n-grams comparison,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 5478 LNCS, pp. 696–700, 2009.

M. Elhadi and A. Al-Tobi, “Use of text syntactical structures in detection of document duplicates,” 3rd Int. Conf. Digit. Inf. Manag. ICDIM 2008, pp. 520–525, 2008.

J. Koberstein and Y.-K. Ng, “Using Word Clusters to Detect Similar Web Documents,” pp. 215–228, 2006.

S. Alzahrani and N. Salim, “Fuzzy semantic-based string similarity for extrinsic plagiarism detection: Lab report for PAN at CLEF 2010,” CEUR Workshop Proc., vol. 1176, 2010.

V. K and D. Gupta, “Study on Extrinsic Text Plagiarism Detection Techniques and Tools,” J. Eng. Sci. Technol. Rev., vol. 9, no. 4, pp. 150–164, 2016.

S. S. Dharani, J. Ganesh, R. Ieshwarya, and M. Sureka, “Extrinsic Plagiarism Detection System for Semantic Replication in Medline,” vol. 4, no. 11, pp. 45–50, 2016.

Z. F. Alfikri and A. Purwarianti, “Detailed Analysis of Extrinsic Plagiarism Detection System Using Machine Learning Approach (Naive Bayes and SVM),” TELKOMNIKA Indones. J. Electr. Eng., vol. 12, no. 11, pp. 7884–7894, 2014.

M. Alsallal, R. Iqbal, S. Amin, A. James, and V. Palade, “An Integrated Machine Learning Approach for Extrinsic Plagiarism Detection,” Proc. - 2016 9th Int. Conf. Dev. eSystems Eng. DeSE 2016, pp. 203–208, 2017.

A. Magooda, A. Mahgoub, M. Rashwan, M. Fayek, and H. Raafa, “RDI System for Extrinsic Plagiarism Detection (RDI_RED),” Work. Notes PAN-AraPlagDet FIRE 2015, pp. 129–131, 2015.

R. Naseem and S. Kurian, “Extrinsic Plagiarism Detection in Text Combining Vector Space Model and Fuzzy Semantic Similarity Scheme,” IRACST – Int. J. Adv. Comput. Eng. Appl., vol. 2, no. 6, pp. 2319–281, 2013.

B. Stein and S. Meyer Zu Eissen, “Intrinsic plagiarism analysis with meta learning,” CEUR Workshop Proc., vol. 276, pp. 45–50, 2007.

B. Stein, N. Lipka, and P. Prettenhofer, “Intrinsic plagiarism analysis,” Lang. Resour. Eval., vol. 45, no. 1, pp. 63–82, 2011.

E. Stamatatos, “Intrinsic Plagiarism Detection Using Character n -gram Profiles,” 2006.

S. Meyer and B. Stein, “LNCS 3936 - Intrinsic Plagiarism Detection,” Advances, pp. 565–569, 2006.

S. Meyer zu Eissen, B. Stein, and M. Kulig, “Plagiarism Detection Without Reference Collections,” pp. 359–366, 2007.

M. Kuznetsov, A. Motrenko, R. Kuznetsova, and V. Strijov, “Methods for intrinsic plagiarism detection and author diarization,” CEUR Workshop Proc., vol. 1609, pp. 912–919, 2016.

L. Seaward and S. Matwin, “Intrinsic Plagiarism Detection using Complexity Analysis,” Stein, B., Rosso, P., Stamatatos, E., Koppel, M., Agirre, E. SEPLN 2009 Work. Uncovering Plagiarism, Authorship, Soc. Softw. Misuse (PAN 2009), pp. 56–61, 2009.

N. Baedlowi, D. A. Adam, and L. Ilmu, “String Matching dengan Menggunakan Algoritma Rabin Karp,” pp. 1–3, 2008.

Salmuasih and A. Sunyoto, “Implementasi Algoritma Rabin Karp untuk Pendeteksian Plagiat Dokumen Teks Menggunakan Konsep Similarity,” Semin. Nas. Apl. Teknol. Inf. 2013, pp. 23–28, 2013.

D. A. Putra, H. Sujaini, and H. S. Pratiwi, “Implementasi Algoritma Rabin-Karp untuk Membantu Pendeteksian Plagiat pada Karya Ilmiah,” J. Sist. dan Teknol. Inf., vol. 1, no. 1, pp. 1–9, 2015.

J. Priambodo, “PENDETEKSIAN PLAGIARISME MENGGUNAKAN ALGORITMA RABIN-KARP DENGAN METODE ROLLING HASH,” J. Inform. Univ. Pamulang, vol. 3, no. 1, pp. 39–45, 2018.

Y. T. Lede, P.A.R.L., Fanggidae, A. dan Polly, “Implementasi Algoritma Rabin-Karp Untuk Mendeteksi Dugaan Plagiarisme Berdasarkan Tingkat Kemiripan Kata Pada Dokumen Teks,” J. Komput. Inform., vol. 2, no. 1, pp. 50–64, 2014.

A. Putera Utama Siahaan and Sugianto, “Analisis k-gram, basis dan modulo rabin-karp sebagai penentu akurasi persentase kemiripan dokumen,” in SENASPRO 2017 | Seminar Nasional dan Gelar Produk, 2017, pp. 198–206.

N. Alamsyah, “Perbandingan Algoritma Winnowing Dengan Algoritma Rabin Karp Untuk Mendeteksi Plagiarisme Pada Kemiripan Teks Judul Skripsi,” Technologia, vol. 8, no. 3, pp. 124–134, 2017.

A. H. Purba and Z. Situmorang, “Analisis Perbandingan Algoritma Rabin-Karp Dan Levenshtein Distance Dalam Menghitung Kemiripan Teks,” J. Tek. Inform. Unika St. Thomas, vol. 02, pp. 24–32, 2017.

P. A. R.-K. dan P. P. dengan A. K.-M.-P. Andres, Christopher, and H. Saloko, “Penelaahan Algoritma Rabin-Karp dan Perbandingan Prosesnya dengan Algoritma Knut-Morris-Pratt,” 2006, no. m, pp. 1–4.

Y. A. Wicaksono, “Analisis Dan Implementasi Algoritma Rabin-Karp Dan Algoritma Stemming Nazief-Adriani Pada Sistem Pendeteksi Plagiat Dokumen,” Bandung, 2012.

T. Mardiana, T. Bharata Adji, and I. Hidayah, “Stemming Influence on Similarity Detection of Abstract Written in Indonesia,” TELKOMNIKA (Telecommunication Comput. Electron. Control., vol. 14, no. 1, p. 219, 2016.

P. Y. Kusmawan, U. L. Yuhana, and D. Purwitasari, “Aplikasi Pendeteksi Penjiplakan pada File Teks dengan Algoritma Winnowing,” pp. 1–11, 2011.

M. Ridho, “Rancang Bangun Aplikasi Pendeteksi Penjiplakan Dokumen Menggunakan Algoritma Biword Winnowing,” PEKANBARU, RIAU, 2013.

A. T. Wibowo, K. W. Sudarmani, and A. moesriami Barmawi, “Comparison Between Fingerprint and Winnowing Algorithm to Detect Plagiarism Fraud on Bahasa Indonesia Documents,” pp. 128–133, 2013.

T. Y. Mahendraputra, “Improvement In Document Similarity Calculation Using Hashing Algorithm And Semantic Analysis On Indonesian Documents,” Universitas Gajah Mada, 2015.

S. Soleman, “Experiments on the Indonesian Plagiarism Detection using Latent Semantic Analysis,” in 2014 2nd International Conference on Information and Communication Technology (ICoICT) Experiments, 2014, pp. 413–418.

T. Mardiana, “Mesin Pengindikasi Kemiripan Untuk Dokumen Berbahasa Indonesia,” Universitas Gajah Mada, 2015.

U. Taufiq, “Pendekatan Deteksi Plagiarisme Berbasis Kutipan Dan Algoritme Kang Untuk Teks Berbahasa Indonesia,” Yogyakarta, 2015.

T. Mardiana, T. B. Adji, and I. Hidayah, “The Comparation of distance-based similarity measure to detection of plagiarism in Indonesian text,” Commun. Comput. Inf. Sci., vol. 516, pp. 155–164, 2015.

J. Kasprzak, M. Brandejs, and M. Kˇripaˇ, “Finding plagiarism by evaluating document similarities,” CEUR Workshop Proc., vol. 502, pp. 24–28, 2009.

M. Koppel and J. Schler, “Computational Methods in Authorship Attribution,” Bulg. J. Agric. Sci., vol. 60, no. 1, pp. 9–26, 2017.

W. W. Cohen, P. Ravikumar, and S. E. Fienberg, “A Comparison of String Distance Metrics for Name-Matching Tasks,” Am. Assoc. Artif. Intelli- gence (www.aaai.org)., vol. 12, no. 1, pp. 57–66, 2003.

D. Gupta, K. Vani, and C. K. Singh, “Using Natural Language Processing techniques and fuzzy-semantic similarity for automatic external plagiarism detection,” in Proceedings of the 2014 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2014, 2014.

A. H. Osman, N. Salim, and M. S. Binwahlan, “Plagiarism Detection Using Graph-Based Representation,” J. Comput., vol. 2, no. 4, pp. 36–41, 2010.

T. W. S. Chow and M. K. M. Rahman, “Multilayer SOM with tree-structured data for efficient document retrieval and plagiarism detection,” IEEE Trans. Neural Networks, vol. 20, no. 9, pp. 1385–1402, 2009.




DOI: http://dx.doi.org/10.33292/ijarlit.v1i2.27

Article Metrics

Abstract view : 161 times
PDF - 48 times

Refbacks

  • There are currently no refbacks.


Citation Analysis

Indexing

DRJI Indexed Journal

Creative Commons License

International Journal Artificial Intelligent and Informatics is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Based on a work at http://ijarlit.org/index.php/IJARLIT.

free
hit counter View My Stats