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All Journal Jurnal Teknik Informatika (JUTIF)
Mychael Maoeretz Engel
Informatics, School of Information Technology, Universitas Ciputra, Indonesia
Computer Science & IT

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Bayesian-Augmented Rule-Based Recommender System Integrated with Customer Relationship Management to Enhance Congregant Retention in Religious Non-Profit Organizations Mychael Maoeretz Engel; Yuwono Marta Dinata
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 5 (2026): JUTIF Volume 7, Number 5, October 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.5.5839

Abstract

This study aims to address the lack of systematic engagement monitoring tools in religious non-profit organizations by developing a CRM-integrated recommender system that supports congregant retention. The research follows a two-phase approach: a systematic literature review (SLR) and a minimum viable product (MVP) implementation. The SLR analyzed 15 scientific articles (2020–2025), confirming that recommender systems in non-profit contexts are predominantly documented for educational, humanitarian, and healthcare sectors, with no prior work targeting religious organizations. Based on these findings, a web-based MVP was developed and deployed at GKI Citraland Surabaya. The system computes a quantitative Attendance Risk Score (RA) using a Bayesian Average formulation that combines individual absence history with a global prior mean, and presents at-risk congregants to administrators who can then initiate semi-manual WhatsApp reminders with one click. Black-box testing across 18 scenarios achieved 100% pass rate. Pilot validation confirmed a 95% reduction in monitoring time and detection of four previously unnoticed at-risk congregants. The primary contributions are: (1) empirical confirmation of a research gap in religious non-profit recommender systems; (2) a replicable Bayesian-augmented rule-based architecture for early warning engagement monitoring; and (3) field evidence of CRM-based retention analytics for community-based non-profit organizations.
Co-Authors Yuwono Marta Dinata