DPJSS: a Maqasid-based data-driven screening system for predatory journal governance detection.

Predatory journals have become a growing threat to research integrity by exploiting researchers through misleading indexing claims, weak peer review practices, spam invitations, and unrealistic publication promises. This innovation introduces DPJSS, a Maqasid-based data-driven screening system designed to assist researchers in identifying and avoiding predatory journals through a structured and ethical evaluation mechanism. The system integrates key indicators, including indexing status, peer review transparency, publication ethics, editorial board verification, APC transparency, and behavioural signals. A structured scoring mechanism was developed to classify journals into legitimate, questionable, and suspected predatory categories, together with corresponding risk levels. DPJSS further incorporates Maqasid al-Shariah ethical filtering, particularly Hifz al-‘Aql (Protection of Knowledge) and Hifz al-Mal (Protection of Wealth), to strengthen ethical governance in scholarly publishing. The prototype system was developed using Google Forms, Google Sheets, automated scoring structures, and dashboard analytics to demonstrate real-time workflow and functionality. A simulation dataset consisting of 30 journal samples was used to test the screening capability of the system. DPJSS supports Sustainable Development Goal (SDG) 4 by promoting ethical and quality academic publishing and contributes to SDG 16 through transparency, accountability, and research integrity in scholarly communication.