PENERAPAN ALGORITMA LEVENSHTEIN DISTANCE UNTUK MISSPELLED WORD PADA PENCARIAN LAGU MELAYU BERBASIS WEBSITE

Batisya, Marcel Rino (2023) PENERAPAN ALGORITMA LEVENSHTEIN DISTANCE UNTUK MISSPELLED WORD PADA PENCARIAN LAGU MELAYU BERBASIS WEBSITE. Undergraduate thesis, Universitas Katolik Musi Charitas Palembang.

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Abstract

Today, people cannot live without music, both indoors and outdoors. Music is a very useful part of human life. It can be used to relax, relieve stress or change the mood. Music is easy to find on many websites today. However, people who like music, especially Malay songs, sometimes forget or misunderstand the title of the song they often hear and sing on various websites. This made it difficult for them to find the title of the Malay song they wanted. This method was not successful because the website could not explain how the spelling of the word in question corresponds to the meaning of the song title. Therefore, the authors rely on the Levenshtein Distance Algorithm to create web-based applications. This algorithm will correct spelling mistakes in song titles, either due to typing speed or typos from users. The Levenshtein Distance between two strings is determined by the least number of transform operations needed to convert one string into another; this matrix, called distance, is used to measure this difference. The operations are insert, delete, and swap. Tests show that correcting song titles that have misspelled words using the Levenshtein Distance algorithm to add and remove characters is effective. Keywords: Music, Malay songs, Website, Levenshtein Distance Algorithm

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Music ; Malay songs ; Website ; Levenshtein Distance Algorithm
Subjects: T Technology > T Technology (General)
T Technology > TD Environmental technology. Sanitary engineering
T Technology > TJ Mechanical engineering and machinery
Divisions: Theses - S1 > Informatics Study Program
Depositing User: Users 1882 not found.
Date Deposited: 03 Mar 2023 02:06
Last Modified: 11 Apr 2023 03:40
URI: http://eprints.ukmc.ac.id/id/eprint/9505

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