Clusterization Model of Hadith Topic in Bukhari Muslim Hadith using BERT Algorithm

Many issues arise in the study of hadith that are trending in the discipline. These issues vary from the digitization of hadith data to proper case studies regarding the approximate narrator chain of a particular hadith. Nonetheless, in this paper, we did not concentrate on learning to estimate, justify, or authenticate a hadith. The focus of this research was more on the use of data mining on hadith datasets. We included the hadith dataset in one of the machine learning tools, namely text clustering. This hadith dataset was used in an experiment for textual clustering of hadith, which was based on the possibility of many words appearing in the hadith text. This study aimed to apply BERT modeling in the clustering of hadith from the book Sahih Bukhari and Muslim. By using NLP techniques, this study explored the possibility of applying the BERT model in clustering these hadiths. The results of this study contribute to the development of more sophisticated and accurate text analysis methods.