APPLICATION OF ARTIFICIAL INTELLIGENCE (AI) AND MACHINE LEARNING (ML) IN THE MUSLIM MODEST FASHION INDUSTRY: A BIBLIOMETRIC REVIEW

Azifatul Hannah; Ninda Ardiani

doi:10.61796/jaide.v2i11.1551

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Azifatul Hannah Muhammadiyah University of Sidoarjo, Indonesia
Ninda Ardiani
nindaardiani@umsida.ac.id
Muhammadiyah University of Sidoarjo, Indonesia

Vol. 2 No. 11 (2025): Journal of Artificial Intelligence and Digital Economy

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November 5, 2025

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Objective: This study aims to analyze the trends and developments of Artificial Intelligence (AI) and Machine Learning (ML) in the fashion industry, with a particular focus on their potential application in the Muslim fashion sector, which remains underexplored. Background: The emergence of AI and ML has become a transformative force across industries, including fashion, offering opportunities to enhance design innovation, production efficiency, and competitiveness in international markets. However, research specific to the Muslim fashion industry is still limited, creating a significant knowledge gap. Method: This study adopts the PRISMA systematic review method to identify and analyze relevant literature. Data were sourced from the Scopus database, with 62 out of 100 selected articles from 2011–2025 meeting the inclusion criteria. The data were further processed and visualized using Microsoft Excel, Biblioshiny, and VOSviewer to map key trends, themes, and collaborations. Results: The findings highlight that AI and ML have been increasingly applied in areas such as trend prediction, supply chain optimization, personalized marketing, and sustainable fashion innovation. Novelty: This study provides valuable insights and practical recommendations for Muslim fashion manufacturers to adopt AI and ML technologies, thereby enhancing innovation, competitiveness, and global market presence.

Hannah, A., & Ardiani , N. (2025). APPLICATION OF ARTIFICIAL INTELLIGENCE (AI) AND MACHINE LEARNING (ML) IN THE MUSLIM MODEST FASHION INDUSTRY: A BIBLIOMETRIC REVIEW. Journal of Artificial Intelligence and Digital Economy, 2(11), 786–807. https://doi.org/10.61796/jaide.v2i11.1551

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