DOI: https://doi.org/10.14710/jtsiskom.8.2.2020.140-149

Temu kembali dokumen sumber rujukan dalam sistem daur ulang teks

Retrieval of source documents in a text reuse system

Department of Informatics, Universitas Kristen Duta Wacana, Indonesia

Received: 17 Oct 2019; Revised: 26 Feb 2020; Accepted: 13 Mar 2020; Available online: 20 Mar 2020; Published: 30 Apr 2020.
Open Access Copyright (c) 2020 Jurnal Teknologi dan Sistem Komputer
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

How to cite (IEEE): N. C. Haryanto, L. D. Krisnawati, and A. R. Chrismanto, "Temu kembali dokumen sumber rujukan dalam sistem daur ulang teks," Jurnal Teknologi dan Sistem Komputer, vol. 8, no. 2, pp. 140-149, Apr. 2020. https://doi.org/10.14710/jtsiskom.8.2.2020.140-149
Citation Format:
Abstract
The architecture of the text-reuse detection system consists of three main modules, i.e., source retrieval, text analysis, and knowledge-based postprocessing. Each module plays an important role in the accuracy rate of the detection outputs. Therefore, this research focuses on developing the source retrieval system in cases where the source documents have been obfuscated in different levels. Two steps of term weighting were applied to get such documents. The first was the local-word weighting, which has been applied to the test or reused documents to select query per text segments. The tf-idf term weighting was applied for indexing all documents in the corpus and as the basis for computing cosine similarity between the queries per segment and the documents in the corpus. A two-step filtering technique was applied to get the source document candidates. Using artificial cases of text reuse testing, the system achieves the same rates of precision and recall that are 0.967, while the recall rate for the simulated cases of reused text is 0.66.
Fulltext View|Download Email colleagues
Keywords: text reuse detection; source retrieval; significant words; local-word weighting scheme
Funding: Universitas Kristen Duta Wacana

Article Metrics:

Article Info
Section: Original Research Articles
Language : ID
Most viewed articles
Decision Support System in Recommending Best Unit in PDAM Tirta Lihou Using Promethee Method Sistem Pengendali Peralatan Elektronik dalam Rumah secara Otomatis Menggunakan Sensor PIR, Sensor LM35, dan Sensor LDR Expert System for Diagnosis of Plant Pest and Disease Horticulture with Forward and Backward Chaining Inference Perancangan Sistem Informasi Rekam Medis Rawat Inap Rumah Sakit Berbasis Web Data Mining using Apriori Algorithm for Product Recommendation for Customers More articles
Most cited articles
Pembuatan Aplikasi Panduan Gizi Seimbang Berbasis Android Dengan Menggunakan Metode Backward Chaining Performance comparison of RSA and AES to SMS messages compression using Huffman algorithm People counter on CCTV video using histogram of oriented gradient and Kalman filter methods Prediction of Call Drops in GSM Network using Artificial Neural Network Desain dan Implementasi Sistem Pembelajaran Jarak Jauh Di Program Studi Sistem Komputer More cited articles
  1. P. Clough, R. Gaizauskas, S. Piao and Y. Wilks, "METER: MEasuring TExt Reuse," in 4th Annual Meeting of the Association for Computational Lingustics, Stroudsburg, United States, Jul. 2002, pp. 152-159. doi: 10.3115/1073083.1073110
  2. L. D. Krisnawati and K. U. Schülz, "Significant word-based text alignment for text reuse detection," in International Conference on Research and Innovation in Computer, Electronics, and MAnufacturing Engineering, Bali, Indonesia, Feb. 2017, pp. 7-12
  3. L. D. Krisnawati, "The use of phraseword and local-weighted terms as features for text reuse and plagiarism detection," in Seminar Hasil Penelitian Bagi Civitas Akademika UKDW, Yogyakarta, Indonesia, Nov. 2017, pp. 27-44
  4. M. Potthast et al., "Overview of the 6th international competition on plagiarism detection," in CLEF 2014 Evaluation Labs and Workshop, Sheffield, UK, Sept. 2014, pp. 845-876
  5. L. D. Krisnawati and K. Schülz, "Plagiarism detection for Indonesian texts," in International Conference on Information Integration and Web-based Applications & Services, Vienna, Austria, Dec. 2013, pp. 595-599. doi: 10.1145/2539150.2539213
  6. L. D. Krisnawati, "Plagiarism detection for Indonesian texts," Dissertation, Ludwig Maximilian University, Munich, Germany, 2016
  7. K. Leilei, L. Zhimao, Y. Yong, Q. Haoliang, and H. Zhongyuan, "Source retrieval and text alignment corpus," in CLEF 2015 Conference and Labs of the Evaluation Forum, Toulouse, France, Sept. 2015, pp. 1-7
  8. B. Gipp, Citation-based plagarism detection: detecting disguised and cross-language plagiarism using citation pattern analysis. Wiesbaden: Springer, 2014. doi: 10.1007/978-3-658-06394-8
  9. A. F. Suryana, A. T. Wibowo, and A. Romadhany, “Performance efficiency in plagiarism indication detection system using indexing method with data structure 2–3 tree,” in 2nd International Conference on Information and Communication Technology, Bandung, Indonesia, May 2014, pp. 403-408. doi: 10.1109/ICoICT.2014.6914096
  10. A. R. Syahputra, "Implementasi algoritma winnowing untuk deteksi kemiripan," Pelita Informatika Budi Dharma, vol. 9, no. 1, pp. 134-138, 2015
  11. Z. F. Alfikri and A. Purwarianti, "Detailed analysis of extrinsic plagiarism detection system using machine learning approach (naive bayes and svm)," TELKOMNIKA Indonesian Journal of Electrical Engineering, vol. 12, no. 11, pp. 7884-7894, 2014. doi: 10.11591/telkomnika.v12i11.6652
  12. N. Kurniati, A. Rahmatulloh, and R. Qomar, "Web scraping and winnowing algorithms for plagiarism detection of final project titles," Lontar Komputer: Jurnal Ilmiah Teknologi Informasi, vol. 10, no. 2, pp. 73-83, 2019. doi: 10.24843/LKJITI.2019.v10.i02.p02
  13. C. D. Manning, P. Raghavan, and H. Schütze, Introduction to information retrieval. New York: Cambridge University Press., 2009
  14. M. Kiabod, M. N. Dehkordi, and M. Sharafi, "A novel method of significant words identification in text summarization," Journal of Emerging Technologies in Web Intelligence, vol. 4, no. 3, pp. 252-258, 2012. doi: 10.4304/jetwi.4.3.252-258
  15. C. Basile, D. Benedetto, E. Caglioti, G. Cristadoro, and M. D. Esposti, "A plagiarism detection procedure in three steps: selection, matches and squares," in 3rd Workshop on Uncovering Plagiarism, Authorship and Social Software Misuse, San Sebastian, Spain, Sept. 2009, pp. 1-9

Last update:

  1. Paper Recommendation for Research References in Data Mining using Content-Based Filtering

    Khoerun Nissa Muflih Hunna, Faiza Renaldi, Irma Santikarama. 2022 International Conference on Science and Technology (ICOSTECH), 2022. doi: 10.1109/ICOSTECH54296.2022.9829112

Last update: 2025-04-05 02:17:23

No citation recorded.