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All Journal Jurnal Teknimedia: Teknologi Informasi dan Multimedia International Journal of Engineering, Science and Information Technology
Ahmad Nurul Fajar
Universitas Bina Nusantara
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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A MACHINE LEARNING SYSTEM ARCHITECTURE FOR PROACTIVE CUSTOMER CHURN PREDICTION Ricky Pieter Palembangan; Ahmad Nurul Fajar
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2026): June 2026
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v7i1.377

Abstract

The hyper-competitive credit card industry faces growing challenges from digital disruption and evolving consumer expectations, demanding a shift from reactive to proactive customer retention strategies. Traditional reactive approaches prove ineffective as customer decisions often reach irreversible stages before intervention. This study aims to develop and evaluate a comprehensive data-driven framework for predicting customer churn at PT XYZ, a leading Indonesian banking institution, and design a scalable system architecture with CRM integration and real-time analytics dashboard for operational deployment. Following the CRISP-DM framework, we comparatively evaluate Logistic Regression, Decision Tree, and Random Forest using a dataset of 11,314 customer records. Model performance evaluation encompasses multiple metrics including Accuracy, Precision, Recall, F1-Score, AUC. Random Forest algorithm demonstrated superior performance, achieving an AUC of 0.98 and accuracy of 97 percent. Feature importance analysis revealed customer transaction inactivity and credit utilization patterns as the most critical churn predictors, with transaction count contributing 41.59% importance score. The research successfully establishes a robust foundation for data-driven customer retention strategies, providing PT XYZ with a comprehensive blueprint for institutionalizing proactive retention strategies that can minimize revenue losses and secure competitive advantages in an increasingly dynamic market environment.
UX Matters: Unlocking QRIS Adoption among MSMEs in the Greater Jakarta Area Muhammad Daffa Ramadhan; Ahmad Nurul Fajar
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1337

Abstract

This study investigates the influence of User Experience (UX) dimensions, integrated with the Technology Acceptance Model (TAM), on the adoption intention of Micro, Small, and Medium Enterprises (MSMEs) in the Greater Jakarta area toward the Quick Response Code Indonesian Standard (QRIS). The research examines functional qualities, which consist of Efficiency, Perspicuity, and Dependability, alongside hedonic qualities, represented by Stimulation and Novelty, as well as Trust, which serves as an essential construct in the adoption process of financial technologies. These factors were evaluated as direct predictors of adoption behaviour, while Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) were employed as mediating variables to capture the mechanisms underlying the relationships, consistent with TAM’s theoretical framework. Data were collected from 400 MSMEs across various industries in the region, and analysis was conducted using Partial Least Squares–Structural Equation Modelling (PLS-SEM). The empirical results demonstrate that Efficiency strongly drives PU, emphasising the critical role of task performance and functional reliability in shaping perceptions of usefulness. Dependability and Trust significantly improve PEOU, highlighting that stable system performance and confidence in technology providers reduce complexity and foster ease of use. Interestingly, while Stimulation shows a positive and direct impact on Intention to Use, Perspicuity and Novelty yield unexpected negative effects, suggesting that overly simple or overly unfamiliar experiences may hinder rather than encourage adoption. Furthermore, PU and PEOU are shown to mediate several causal paths, reinforcing TAM’s theoretical assumptions and underscoring the value of integrating UX considerations into classical acceptance models. The final structural model exhibits strong explanatory power, with an R² of 0.903 for Intention to Use, indicating the robustness of the integrated framework and confirming the effectiveness of combining UX dimensions with TAM in explaining QRIS adoption behaviour among MSMEs.
Co-Authors Muhammad Daffa Ramadhan Ricky Pieter Palembangan