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

Abstract

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.

Developing Medical Virtual Teaching Assistant Based on Speech Recognition Technology

“…The Levenshtein algorithm is a distance measure due to the development of a scientist who came from Russia in 1965 named Vladimir Levenshtein [17]. Programmers are more familiar with Levenshtein for measuring the distance between two strings.…”

Penerjemahan Bahasa Indonesia ke Bahasa Minang dari Optical Character Recognition dengan Menggunakan Algoritme Edit Distance

“…Penelitian Wint et al juga menggunakan Levenshtein Distance untuk melalukan perbaikan ejaan pada dataset sosial media dengan tingkat akurasi 90% (Wint et al 2017). Levenshtein Distance juga digunakan untuk melakukan autocomplete dan spell checking dalam proses pencarian data perpustakaan (Yulianto et al 2018). Cahyono dalam penelitiannya menggunakan algoritme Jaro-Winkler dan algoritme Paragraph Vector dalam melakukan perbandingan kemiripan dokumen pada dokumen ilmiah.…”

Pengembangan dan Implementasi Program Aplikasi Koreksi Ejaan untuk Membantu Guru Memeriksa Naskah Soal

“…Aplikasi spell checker juga dapat memiliki spesifikasi tertentu sesuai dengan tujuan dan kebutuhan masing-masing aplikasi. Spell checker dapat menjadi sistem yang terintegrasi dengan sistem lainnya seperti terintegrasi pada sistem pencarian diperpustakaan (Yulianto, M. M., Arifudin, R., & Alamsyah, A., 2018). Sistem tersebut digunakan untuk menampilkan saran kata atau auto complete kata yang ditulis atau mencari kata yang sesuai walaupun terjadi kesalahan pengetikan.…”