Volume 8, Issue 1, June 2019, Page: 18-31
Informatian Retrieval for Popular Words in Bahasa Translation of Al Quran and Hadith Bukhori Using Enhance Confix Stripping (ECS) Stemming
Tristyanti Yusnitasari, Faculty of Computer Science and Information Technology, Gunadarma University, Depok, Indonesia
Irfan Humaini, Faculty of Computer Science and Information Technology, Gunadarma University, Depok, Indonesia
Lily Wulandari, Faculty of Computer Science and Information Technology, Gunadarma University, Depok, Indonesia
Diana Ikasari, Faculty of Computer Science and Information Technology, Gunadarma University, Depok, Indonesia
Received: Oct. 11, 2018;       Accepted: May 23, 2019;       Published: Aug. 15, 2019
DOI: 10.11648/j.ajsea.20190801.13      View  112      Downloads  13
Abstract
This paper discusses other ways that can be used to obtain information about information seeking for popular words in Qur’an and Hadith language translations. Popular words like the example of searching for the word "corruption" will be very difficult to find in translations of the Qur’an and Hadith. Information about popular words in the translation of the Qur’an and Hadith is needed so as to facilitate the search. In the research carried out was to obtain information about popular words first and then find the word synonym. This study uses Information Retrieval Technique which is a tokenizing process, stopword removal and stemming. The stemming method used in this study is ECS (Enhance Confix Stripping). Information retrieval is used to display some of the Qur'an and hadith that relate to the keywords searched for according to certain criteria. The dataset used in this study comes from the translation of the Ministry of Religion of the Republic of Indonesia.
Keywords
Informasi, Information Retrieval, Al Quran, Hadith, ECS
To cite this article
Tristyanti Yusnitasari, Irfan Humaini, Lily Wulandari, Diana Ikasari, Informatian Retrieval for Popular Words in Bahasa Translation of Al Quran and Hadith Bukhori Using Enhance Confix Stripping (ECS) Stemming, American Journal of Software Engineering and Applications. Vol. 8, No. 1, 2019, pp. 18-31. doi: 10.11648/j.ajsea.20190801.13
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
Adriani, M., Asian, J., Nazief, B. Tahaghoghi, S. M. M., Williams, H. E. 2007. Stemming Indonesian: A Confix-Stripping Approach. Transaction on Asian Langeage Information Processing.
[2]
Agusta, Ledy. Comparison of Algortima Stemming Porter With Nazief & Adriani Algorithm For Stemming Indonesian Text Document. Satya Wacana Christian University. 2009.
[3]
Akram Roshdi, Akram Roohparvar. Review: Information Retrieval Techniques and Applications, International Journal of Computer Networks and Communications Security, VOL. 3, NO. 9, 373-377, September 2015.
[4]
Baeza R. Y., Neto R., Modern Information Retrieval, Addison Wesley-Pearson international edition, Boston. US. USA, 1999.
[5]
Berry, M. W. & Kogan, J. 2010. Text Mining Aplication and theory.
[6]
Broto Poernomo T. P, Ir. Gunawan, Information Retrieval System Search Similarities AlQur'an Translation Version in Indonesian with Query Expansion from Tafsirnya IDeaTech, ISSN: 2089-1121, 2015.
[7]
Bridge, C. 2011. Unstructured Data and the 80 Percent Rule.
[8]
Fatkhul Amin, Information Retrieval System with Vector Space Model Method, Journal of Business Information Systems 02, 2012.
[9]
Feldman, R & Sanger, J. 2007. The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data. Cambridge University Press: New York.
[10]
Jasman Pardede, Mira M Barmawi, Wildan D Pramono, Implementation of Generalized Vector Space Model Method In Information Retrieval Applications, No.1, Vol. 4, ISSN: 2008-5266, January - April 2013.
[11]
Jovita, Linda, Andrei Hartawan, 2015, Using Vector Space Model in Question Answering System, International Conference on Computer Science and Computational Intelligence (ICCSCI 2015).
[12]
Kendall, J. E. & Kendall, K. E. 2010. Analisis dan Perancangan Sistem. Jakarta: Indeks.
[13]
Lukman Fakih Lidimilah, 2017, Question Answering Terjemah Al qur’an Menggunaka Named Entity Recognition, Jurnal Ilmiah Informatika Volume 2 No. 2.
[14]
Mandala, Rila dan Hendra Setiawan. Peningkatan Performansi Sistem Temu KembaliInformasi dengan Perluasan Query Secara Otomatis, Laboratorium Keahlian Informatika teori Department Teknik Informatika, Institut Teknologi Bandung, 2006.
[15]
Manning, Christopher D., Prabhakar Raghavan,. Introduction to Information Retrieval. Cambridge University Press, Cambridge, England, 2009.
[16]
McEnery, A. M., Wilson, A. 2001. Corpus Linguistics. Edinburgh: Edinburgh University Press.
[17]
Moral, C., Antonio, A., Imbert, R., Rmirez J.: A survey of stemming algorithms in information retrieval. Inf. Res.: Int Electron. J. 19 (1), 2014).
[18]
Nesdi E. Rozanda, Arif Marsal, Kiki Iswanti, Design of Hadist Information Systems Using Technique of Retrieval of Vector Space Model Information, ejournal.uin-suska.ac.id, 20014.
[19]
Salton G, Buckley C. (1988). Term-weighting approaches in automatic text retrieval. Information Processing and Management, 24 (5), 513-523. https://doi.org/10.1016/0306-4573 (88) 90021-0
[20]
Saraswati, N. W, 2011. Text Mining dengan Metode Naive Bayes Classifier dan Support Vector Machines untuk Sentiment Analysis. Universitas UDAYANA
[21]
Subari, Ferdinandus, Health Information Retrieval System For Medical Treatment Using Space Vector Method (VSM) Method Based on WebGis, ISSN 2089-1083, Snatika 2015.
[22]
Surya Agustian, Imelda Sukma Wulandari, Qur'an Retrieval System Web-based Indonesian Translation with Reorganization of Corps, KNSI 2013, ISBN 978-602-17488-0, 2013.
[23]
Tala, Fadillah Z. 2003. A Study of Stemming Efects on Information Retrieval in Bahasa Indonesia.
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