Machine Learning in Islamic Finance

This study aims to see the development of research on the topic of "Machine Learning in Islamic Finance" and research plans that can be carried out based on journals published on the theme. This research uses a qualitative method with a bibliometric analysis approach. The data used is secondary data with the theme "Machine Learning in Islamic Finance" which comes from the Dimension database with a total of 30 journal articles. Then, the data is processed and analyzed using the VosViewer application with the aim of knowing the bibliometric map of research development "Machine Learning in Islamic Finance" in the world. The results of the study found that there are 5 clusters with the most used words are finance, model, technology, Islamic bank, machine, industry, fintech, and system. Then, the research path topics related to Machine Learning in Islamic Finance are Machine Learning for Islamic Bank Efficiency, Machine Learning in Islamic Fintech, Customer Behavior and Machine Learning, Islamic Economic Growth and AI Innovation, and Blockchain for Global Zakat Distribution.