Authors:

Halimah Tus Sadiah, Muhamad Saad Nurul Ishlah, Nisa Najwa Rokhmah

Abstract:

“Dictionary of medicine in the form of a thick book has many disadvantages, one of which is impractical. This is the reason for Indonesian developers to create drugs e-Dictionary. But the drugs e-Dictionary that has been developed is still in the form of a letter index so that users must search the terms one by one in sequential order. This has become so inefficient and ineffective that it is necessary to add a search function and query suggestion feature to the drug e-dictionary. The purpose of this study is to build a query suggestion facility on drugs e-Dictionary using the Levenshtein Distance algorithm. The stages of this research consist of the Development of web-based drugs e-Dictionary, Implementation of the Levenshtein Distance Algorithm, Query Suggestion Testing, and Usage. Based on the results of the implementation of the Levenshtein Distance algorithm and test results, Drugs e-Dictionary can evaluate words that are not in the database. The query suggestion function works by producing the closest word output contained in the database.”

Keywords

Keyword Not Available

Downloads:

Download data is not yet available.

References

  • [1] Departemen Kesehatan RI. Tanggung Jawab Apoteker Terhadap Keselamatan Pasien (Patient Safety ). Jakarta: Direktorat Bina Farmasi Komunitas Dan Klinik Ditjen Bina Kefarmasian Dan Alat Kesehatan Departemen Kesehatan RI. 2008.
  • [2] Y. Song, & Li-wei He. 2010. Optimal Rare Query Suggestion With Implicit User. ACM Journals.pp: 901-910.
  • [3] S. Jiang, S. Zilles, & R. Holte. 2008. Query suggestion by query search: a new approach to user support in web search [Online]. [Cited 2018 August 1]. Available from www.cs.uregina.ca/~zilles/jiangZH09.pdf
  • [4] Y. Song, D. Zhou., & L.W. He. 2011. Post-ranking-query-suggestion-by-diversifying-searchresul [Online]. [Cited 2018 August 1]. Available from https://www.microsoft.com/id-id/: https://www.microsoft.com/en-us/research/publication/post-ranking-query-suggestionbydiversifying-search-results/
  • [5] J.-M.Yangy, R. Cai, F. Jingz, S.Wangy, L. Zhangy, & W.Y.Ma. 2008. Search-based Query Suggestion.[Online] [Cited 2018 August 1]. Available from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.159.3499&rep=rep1&type=pdf
  • [6] Q. Mei, D. Zhou & K Church 2008. Query Suggestion Using Hitting Time [Online]. [Cited 2018 August 1]. Available from https://www.microsoft.com/enus/ research/wpcontent/uploads/2017/01/sugg.pdf
  • [7] H. Cao, D. Jiang,J. Pei, Q. He, Z. Liao, E. Chen, & H. Li. 2008. Context-Aware Query Suggestion by Mining Click-Through [Online]. [Cited 2018 August 1]. Available from https://www.cs.sfu.ca/~jpei/publications/QuerySuggestion-KDD08.pdf
  • [8] Z.-J. Zha, L. Yang, T. Me., M. Wang, & Zengfu. Visual Query Suggestion. ACM Journals.
  • pp. 15-24. 2009.
  • [9] S. Bathia, D. Majumdar, & P. Mitra. Query Suggestions in the Absence of Query Logs. ACM Journals, pp. 1-10.2011.
  • [10] K.N. Ngafidin & H. Wibawanto. Implementasi Fitur Autocomplete dan Algoritma Levenshtein Distance untuk Meningkatkan Efektivitas Pencarian Kata di Kamus Besar Bahasa Indonesia (KBBI). Jurnal Teknik Elektro. Vol. 7, No. 1, pp.1-6. 2015
  • [11] R Pressman dan B.R. Maxim. Software Engineering a Practitioners approach. McGraw-Hill Education : New York. 2014.
  • [12] J Satzinger, R. Jackson, & S. Burd. System Analysis and Design in a changing World. USA: Course Technology Cengage Learning. 2010.
  • [13] Ikatan Apoteker Indonesia. ISO Informasi Spesialite Obat Indonesia. Vol 52. 2019. Jakarta : Isfi Penerbitan.2019
  • [14] Z.Afriansyah, D.Puspitaningrum, & Ernawati. Rancang Bangun Aplikasi Pencocokan DNA Manusia Menggunakan Algoritma Levenshtein Distance (Studi Kasus: Dna Kanker Hati Manusia). Jurnal Rekursif . Vol. 3, No. 2,pp. 61-67.2015.
  • [15] B. Pratama & S. Pamungkas, Analisis Kinerja Algoritma Levenshtein Distance Dalam Mendeteksi Kemiripan Dokumen Teks. Jurnal Log!k@ . Vol. 6, No. 2, pp. 131-143.2016
  • [16] T. Aprilianto, & A. Badawi. Sistem Koreksi Kata Dan Pengenalan Struktur Kalimat Berbahasa Indonesia Dengan Pendekatan Kamus Berbasis Levenshtein Distance. Jurnal SPIRIT. Vol. 9, No. 1, pp 48-61. 2017.
  • [17] R. Haldar, & D. Mukhopadhyay. 2011. Levenshtein Distance Technique in Dictionary Lookup Methods: An Improved Approach [Online]. [Cited 2018 August 1]. Available from
  • [18] R. Mishra, & N. Kaur. A Survey of Spelling Error Detection and Correction Techniques. International Journal of Computer Trends and Technology. Vol. 3, No. 4, pp. 372-374. 2013
  • [19] N. Ariyani, N., R. Sutardi, & Ramadhan. Aplikasi Pendeteksi Kemiripan Isi Teks Dokumen Menggunakan Metode Levenshtein Distance. semanTIK.Vol. 2, No. 1,pp. 279-286. 2016.
  • [20] M. Navin, Pankaja R. Performance Analysis of Text Classification Algorithms using Confusion Matrix. International Journal of Engineering and Technical Research (IJETR). Vol. 6, No. 2,pp. 75-78. 2016

PDF:

https://jurnal.harianregional.com/lontar/full-53530

Published

2019-12-30

How To Cite

SADIAH, Halimah Tus; SAAD NURUL ISHLAH, Muhamad; NAJWA ROKHMAH, Nisa. Query Suggestion on Drugs e-Dictionary Using the Levenshtein Distance Algorithm.Lontar Komputer : Jurnal Ilmiah Teknologi Informasi, [S.l.], p. 193-202, dec. 2019. ISSN 2541-5832. Available at: https://jurnal.harianregional.com/lontar/id-53530. Date accessed: 28 Aug. 2025. doi:https://doi.org/10.24843/LKJITI.2019.v10.i03.p07.

Citation Format

ABNT, APA, BibTeX, CBE, EndNote - EndNote format (Macintosh & Windows), MLA, ProCite - RIS format (Macintosh & Windows), RefWorks, Reference Manager - RIS format (Windows only), Turabian

Issue

Vol. 10, No. 3 December 2019

Section

Articles

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License