Calculation of Similarity between MUI Fatwas: A Comparison of Text Extraction Features and String Matching Algorithms
DOI:
https://doi.org/10.12962/j22759970.v5i1.1226Keywords:
Fatwa MUI, Word Extraction, Jaccard Similarity, Cosine Similarity, Euclidean Similarity, Dice SimilarityAbstract
Fatwas, as religious rulings issued by the Indonesian Ulama Council (MUI), play a crucial role in guiding the Muslim community. This research aims to analyze the similarity between these fatwas, contributing to the field by comparing various similarity methods. The dataset includes 380 fatwa titles collected from the official website of the National Sharia Council of the Indonesian Ulama Council. The research follows a structured methodology: starting with data collection, followed by text pre-processing involving punctuation removal, stemming, and stop word elimination. Word extraction techniques such as Bag of Words (BoW), TF-IDF (Term Frequency-Inverse Document Frequency), and BERT (Bidirectional Encoder Representations from Transformers) are then applied. Similarity is calculated using Jaccard Similarity, Cosine Similarity, Euclidean Distance, and Dice Coefficient. The results show that Cosine Similarity combined with TF-IDF achieves the highest performance with an F1 Score of 0.299. This study is novel in its comprehensive comparison of multiple similarity methods applied to MUI fatwas, providing valuable insights for researchers and practitioners in Natural Language Processing (NLP).References
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