Autocomplete and Spell Checking Levenshtein Distance Algorithm To Getting Text Suggest Error Data Searching In Library

Muhamad Maulana Yulianto, Riza Arifudin, Alamsyah Alamsyah


Nowadays internet technology provide more convenience for searching information on a daily. Users are allowed to find and publish their resources on the internet using search engine. Search engine is a computer program designed to facilitate a user to find the information or data that they need. Search engines generally find the data based on keywords they entered, therefore a lot of case when the user can’t find the data that they need because there are an error while entering a keyword. Thats why a search engine with the ability to detect the entered words is required so the error can be avoided while we search the data. The feature that used to provide the text suggestion is autocomplete and spell checking using Levenshtein distance algorithm. The purpose of this research is to apply the autocomplete feature and spell checking with Levenshtein distance algorithm to get text suggestion in an error data searching in library and determine the level of accuracy on data search trials. This research using 1155 data obtained from UNNES Library. The variables are the input process and the classification of books. The accuracy of Levenshtein algorithm is 86% based on 1055 source case and 100 target case.


Autocomplete, Spell Checking, Levenshtein Distance, Library Automation, Data Searching

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Martínez, L.S., & Sánchez, D. (2016). Evaluating the suitability of Web search engines as proxies for knowledge discovery from the Web. Procedia Computer Science, 96, 169-178.

Awny, S., & Amal A, M. (2017). IBRI-CASONTO: Ontology-based semantic search engine. Egyptian Informatics Journal, 18, 181-192.

Yao, Z. (2013). Implementation Of The Autocomplete Feature Of The Textbox Based On Ajax And Web Service. Journal of Computers, (8) 9 : 2197-2203.

Rubio, M. 2015. A Consensus Algorithm for Approximate String Matching. Iberoamerican Conference on Electronics Engoneering and Computer Science, 7, 322-327.

Ayad, L. A., Barton, C., & Pissis, S. P. (2017). A faster and more accurate heuristic for cyclic edit distance computation. Pattern Recognition Letters, 88, 81-87.

Umar, R., Hendriana, Y., & Budiyono, E. (2015). Implementation of Levenshtein Distance Algorithm for E-Commerce of Bravoisitees Distro. International Journal of Computer Trends and Technology (IJCTT), 27 (3), 131-136.

Putra, M. E. W., & Suwardi, I. S. (2015). Structural off-line handwriting character recognition using approximate subgraph matching and levenshtein distance. Procedia Computer Science, 59, 340-349.

Nejja, M. & Yousfi, A. (2015). The Context In Automatic Spell Correction. The International Conference on Advanced Wireless, Information, and Communication Technologies (AWICT), 73, 109-114.

Andrade, G., Teixeira, F., Xavier, C. R., Oliveira, R. S., Rocha, L. C., & Evsukoff, A. G. (2012). HASCH: high performance automatic spell checker for Portuguese texts from the web. Procedia Computer Science, 9, 403-411.

Yudie, I., Mustafid, P. & Sugiharto, A. (2011). Perancangan Sistem Informasi Perpustakaan Berbasis Web Application. Jurnal Sistem Informasi Bisnis, 01, 70-73.

Yudhistira, E., Purwinarko, A., & Wusqo, I. U. (2016). Implementasi Restful Web Service Menggunakan AsyncTask pada Aplikasi Library Automation Berbasis Android. Seminar Nasional Ilmu Komputer (SNIK 2016), 286-292.

Nurendah, Y., & Mulyana, M. (2013). Analisis Pengaruh Kualitas Pelayanan Perpustakaan Terhadap Kepuasan dan Hubungannya dengan Loyalitas Mahasiswa. Jurnal Ilmiah Manajemen Kesatuan, 1(1): 93-112.

Janowski, T., & Mohanti, H. (2010). Distributed Computing and Internet Technology. India: Springer.

Desai, N. & Narvekar M. (2015). Normalization of Noisy Text Data. International Conference on Advanced Computing Technologies and Applications (ICACTA), 45, 127-132.

Mary, R., Nishikant, A. S., & Iyengar, N. C. S. (2014). Use of Edit Distance Algorithm to Search a Keyword in Cloud Environment. International Journal of Database Theory and Application, 7(6), 223-232.

Mishra, R., & Kaur, N. (2013). A Survey of Spelling Error Detection and Correction Techniques. International Journal of Computer Trends and Technology, 4(3), 372-374.

Chowdhury, S.D., Bhattacharya U., & Parui S.K. (2013). Online Handwriting Recognition Using Levenshtein Distance Metric. Document Analysis and Recognition (ICDAR),79-83.

Patel, U.A., & Jain N.K. (2013). New Idea in Waterfall Model for Real Time Software Development. International Journal of Engineering Research & Technology (IJERT), 2(4), 115.

Pressman, R. S. (2005). Software engineering: a practitioner's approach. Palgrave Macmillan.

Nugroho, Z. A., & Arifudin, R. (2015). Sistem Informasi Tracer Study Alumni Universitas Negeri Semarang Dengan Aplikasi Digital Maps. Scientific Journal of Informatics, 1(2), 153-160.

Putra, A. T. (2015). Pengembangan E-Lecture menggunakan Web Service Sikadu untuk Mendukung Perkuliahan di Universitas Negeri Semarang. Scientific Journal of Informatics, 1(2), 168-176.

Vedayoko, L. G., Sugiharti, E., & Muslim, M. A. (2017). Expert System Diagnosis of Bowel Disease Using Case Based Reasoning with Nearest Neighbor Algorithm. Scientific Journal of Informatics, 4(2), 134-142.

Purwinarko, A., & Sukestiyarno, Y. L. (2015). Model Expertise Management System di Universitas Negeri Semarang. Scientific Journal of Informatics, 1(2), 177-184.

Mustaqbal, M. S., Firdaus, R. F., & Rahmadi, H. (2016). Pengujian Aplikasi Menggunakan Black Box Testing Boundary Value Analysis (Studi Kasus: Aplikasi Prediksi Kelulusan SMNPTN). Jurnal Ilmiah Teknologi Informasi Terapan, 1(3), 31-36.

Bo, W., & Han-bo, W. (2010). Implementation of Auto Complete Based on Jquery. Journal of SanMenXia Polytechnic, 9(3), 102-126.

Kamayani, M., Reinanda, R., Simbolon, S., Soleh, M. Y., & Purwarianti, A. (2011). Application of document spelling checker for Bahasa Indonesia. Advanced Computer Science and Information System (ICACSIS), 249-252.

Kaur, A., Singh, P., & Rani, S. (2014). Spell Checking and Error Correcting System for text paragraphs written in Punjabi Language using Hybrid approach. International Journal of Engineering and Computer Science, 3(09), 8030-8032.



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