Open AccessAnalisis Metode Representasi Teks Untuk Deteksi Interelasi Kitab Hadis: Systematic Literature Review
Author(s) -
Amelia Devi Putri Ariyanto,
Chastine fatichah,
Agus Zainal Arifin
Publication year - 2021
Publication title -
jurnal resti (rekayasa sistem dan teknologi informasi)
Language(s) - English
Resource type - Journals
ISSN - 2580-0760
DOI - 10.29207/resti.v5i5.3499
Subject(s) - sentence , meaning (existential) , computer science , embedding , natural language processing , classifier (uml) , representation (politics) , artificial intelligence , linguistics , similarity (geometry) , epistemology , philosophy , law , politics , political science , image (mathematics)
Hadith is the second source of reference for Islamic law after the Qur'an, which explains the sentences in the Qur'an which are still global by referring to the provisions of the Prophet Muhammad SAW. Classification of text documents can also be used to overcome the problem of interrelation between the Qur'an and hadith. The problem of interrelation between books of hadith needs to be done because some hadiths in certain hadith books have the same meaning as other hadith books. This study aims to analyze the development of text representation and classification methods suitable to overcome similarity meaning problems in detecting interrelationships between hadith books. The research method used is Systematic Literature Review (SLR) sourced from Google Scholar, Science Direct, and IEEE. There are 42 pieces of literature that have been studied successfully. The results showed that contextual embedding as the newest text representation method considered word context and sentence meaning better than static embedding. As a classification method, the ensemble method has better performance in classifying text documents than using only a single classifier model. Thus, future research can consider using a combination of contextual embedding and ensemble methods to detect interrelationships between books of hadith.