Abstract
Computer science development, especially machine learning, is a thriving innovation essential for education. It makes the process of teaching and learning more accessible and manageable and also promotes equality. The positive influence of machine learning can also be felt in Islamic studies, particularly in Hadith studies. This literature review highlights the role of machine learning in managing research regarding Hadith studies that have been published and categorizing it by their research topics, language & corpus, and the machine-learning algorithms. This article review has been conducted on 48 previously published hadith study journals. Then, we summarize existing trends, including trending topics, common language & corpus, and general algorithms often used in previous hadith-related reviews. This article aims to give new insight to help the broad community of researchers interested in these narrations to create fresh and further research with the uncommon topic, language & corpus, and algorithms. Furthermore, this article is also expected to contribute to academics and practitioners as a guide for conducting future research on the application of computer science in Hadith studies. We conclude that the most frequently discussed topic is Hadith Classification at 33.33%, the most widely used language is Arabic at 43.75%, and the most commonly used algorithm is SVM at 12.5%. In addition, the dataset mainly used is a public dataset by Al-Bukhari at 30.53%
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BS search for the topic that will be used in the SLR journal. AR and AT compile the introduction section based on the journal topic. EA and MZ conduct a review and correction of the introduction section. BS and AR determine the method to be used in the research. BS design and determine the Research Question (RQ) that will be used to guide the literature search and extraction process. BS, AR and AT discuss and provide input on the RQ to make the research more focused. EA and MZ provide guidance for the RQ to be more measurable, and directed towards understanding the state-of-the-art research on the research topic. BS and AR define the criteria for Quality Assessments (QA) used in selecting journals from the search results. BS and AR determine the digital library used to search for journal keywords. AT provide input to add digital libraries. BS and AR define the steps for searching for journals using search keywords. BS Conduct a search using title and abstract keywords and filter based on topic, time and journal type. BS Select journals from the search results based on inclusion and exclusion criteria. BS gather, group and store the data from the selected journals into an Excel file. BS perform data extraction by reading and filtering the journals based on RQ and QA. BS and AR display the literature review results of the journals obtained from data extraction and create visualizations and display the results in the form of tables and graphs. EA and MZ conduct a review and correction of the way the visualization results are displayed. BS and AR Add a discussion section containing an analysis based on the SLR journal visualization results. AR and AT conduct a review and correction of the discussion section. BS and AR add a limitation section that contains the scope limitations of the SLR research. EA and MZ conduct a review and correction of the limitation section. BS draw conclusions based on the RQ, discussion results, and analysis. AR, AT, EA and MZ conduct a review and correction of the conclusion. BS compile the abstract section, which is a summary of all parts of the SLR. AR, AT, EA and MZ conduct a review and correction of the abstract section.
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Sulistio, B., Ramadhan, A., Abdurachman, E. et al. The utilization of machine learning on studying Hadith in Islam: A systematic literature review. Educ Inf Technol 29, 5381–5419 (2024). https://doi.org/10.1007/s10639-023-12008-9
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DOI: https://doi.org/10.1007/s10639-023-12008-9