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Exploring the relationship between hadith narrators in Book of Bukhari through SPADE algorithm
Rahmadi Yotenka1, Sekti Kartika Dini1, Achmad Fauzan1
1Department of Statistics, Universitas Islam Indonesia, Yogyakarta, Indonesia.
This study analyzes hadith narrator relationships using Sequential Pattern Discovery using Equivalence Classes (SPADE). It details data preprocessing and pattern analysis for understanding hadith validity.
Area of Science:
- Islamic Studies
- Computer Science
- Data Mining
Background:
- Hadith are crucial legal resources in Muslim society.
- Traditional hadith research often focuses on content, neglecting narrator relationships.
- The chain of narrators (sanad) is fundamental to hadith authenticity and validity.
Purpose of the Study:
- To analyze the relationship patterns among hadith narrators.
- To develop and present a methodology for extracting narrator relationship patterns from hadith data.
- To provide a novel approach to assessing hadith validity through narrator network analysis.
Main Methods:
- Utilized Sequential Pattern Discovery using Equivalence Classes (SPADE) algorithm.
- Developed Algorithm 1 for data preprocessing to isolate narrator data from content.
- Developed Algorithm 2 for analyzing narrator relationship patterns using SPADE.
Main Results:
- Successfully separated narrator data from mixed content in hadith books.
- Identified patterns in hadith narrator relationships.
- Provided a systematic approach to analyzing narrator networks.
Conclusions:
- The SPADE algorithm is effective for uncovering patterns in hadith narrator relationships.
- The methodology enhances the understanding of hadith authenticity by focusing on narrator connections.
- This research offers a new computational approach to hadith studies.
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