Modeling MSMEs Halal Certification Intent Using Smart Data Analytics and Digital Literacy Insights

The adoption of halal certification among Micro, Small, and Medium Enterprises (MSMEs) is essential to ensure compliance with national regulations and consumer trust, particularly in Muslim-majority nations such as Indonesia. However, certification uptake remains low in underprivileged areas due to limited digital engagement and system access. This study presents a data-driven framework that integrates smart analytics and digital literacy profiling to predict MSMEs’ intent to pursue halal certification. Developed a decision-support model using primary data from 167 culinary MSMEs in Madura, Indonesia, analyzed through Partial Least Squares–Structural Equation Modeling (PLS-SEM) and supplemented by digital readiness indicators. The proposed model evaluates the influence of demographic and turnover factors on halal literacy and certification interest, while also assessing the mediating role of digital awareness. Results show that while business turnover is significantly correlated with halal literacy, demographic variables are not. Critically, digital literacy emerges as a moderating factor influencing the conversion of halal knowledge into actionable certification intent. These findings suggest that technology access and readiness are pivotal in driving certification behavior. The model contributes to the development of intelligent support systems for regulators to identify at-risk MSMEs and deploy targeted digital interventions. Future work will involve the integration of machine learning classifiers to enhance prediction accuracy and explore mobile-based certification support platforms to scale adoption. This research bridges socio-religious compliance with smart technology solutions, offering actionable insights for digital transformation in halal certification ecosystems.