Perbandingan Metode Cosine Similarity Dengan Metode Jaccard Similarity Pada Aplikasi Pencarian Terjemah Al-Qur'an dalam Bahasa Indonesia
DOI:
https://doi.org/10.15575/join.v1i1.12Keywords:
Relevan, Cosine, Jaccard, Nearest Neighbor (K-NN), Al-Qur'anAbstract
Todays there are more applications supporting Al-Qur'an to facilitate such a study, which could be called digital Al-Qur'an. But when using applications digital Al-Qur'an, which has many applications users experience difficulties when searching for a word that users want.This occurs when users misspell a word you want to search and applications that are not yet able to identify or justify the wrong word. In this thesis made the information retrieval system that is used to find information that is relevant to the needs of its users automatically based on conformity to the query of a collection of information.Algoritma used to determine the similarity (degree of similarity) or relevant similarity algoritma, cosine, Jaccard, and nearest neighbor (k-nn) for comparing algoritma that are more relevant to the translation application alquran. The test result proves that the cosine similarity algoritma has the highest value with the percentage of 41% compared with Jaccard 19% algoritma and nearest neighbor (k-nn) 40% on translation of Al-Qur'an as much 6326 document and 33 query different experiments.
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