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Exploring the relationship between hadith narrators in Book of Bukhari through SPADE algorithm.
Yotenka, Rahmadi; Dini, Sekti Kartika; Fauzan, Achmad; Ahdika, Atina.
Afiliação
  • Yotenka R; Department of Statistics, Universitas Islam Indonesia, Yogyakarta, Indonesia.
  • Dini SK; Department of Statistics, Universitas Islam Indonesia, Yogyakarta, Indonesia.
  • Fauzan A; Department of Statistics, Universitas Islam Indonesia, Yogyakarta, Indonesia.
  • Ahdika A; Department of Statistics, Universitas Islam Indonesia, Yogyakarta, Indonesia.
MethodsX ; 9: 101850, 2022.
Article em En | MEDLINE | ID: mdl-36164434
ABSTRACT
As one of the law resources of Muslim society, hadith is very important to learn. Unlike most hadith-related research, which studies more about content, we examine the relationship pattern between hadith narrators. In the study of hadith science, a series of hadith narrators who narrate a hadith is referred to as a sanad. This hadith sanad must be connected to the Prophet as the primary source of a hadith. Therefore, research related to the relationship between narrators is fundamental because it affects the quality and validity of a hadith. This paper analyzes the pattern of hadith narrators using Sequential Pattern Discovery using Equivalence Classes (SPADE). We separate the data of the narrators from the content, whereas, in the hadith books we use, the two are still mixed. This study, therefore, provides detailed information on the steps in the analysis of the patterns of hadith narrators. Some of the highlights of this paper are•Algorithm 1 provides the detailed steps in data preprocessing to obtain the "clean data" needed in analyzing the pattern of narrator relationships.•Algorithm 2 provides a detailed description of analyzing the pattern between hadith narrators using SPADE.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article