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All Journal Jurnal Teknik Industri : Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri Community Engagement and Emergence Journal (CEEJ)
Gultom, Rafly Aqsha
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering

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Decision-Making Analysis on The Credit Card Partnership Program Using Kepner-Tregoe and Smart Technique Approaches Gultom, Rafly Aqsha; Siallagan, Manahan Parlindungan Sarigih
JTI: Jurnal Teknik Industri Vol 11, No 1 (2025): JUNI 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jti.v11i1.37413

Abstract

This study analyzes the root causes of underperformance in PT Bank XYZ’s credit card partnership program with F&B merchants. Using the Kepner-Tregoe (KT) Problem Solving Framework and the SMART (Simple Multi-Attribute Rating Technique), the research adopts an exploratory-descriptive qualitative approach involving Forum Group Discussions (FGDs) with internal stakeholders. The analysis identified two main problems: weak internal coordination between the EDC and Marketing teams, and low merchant and cashier engagement in executing promotional programs. Three alternative solutions were evaluated: (1) Integrated Merchant Engagement Program, (2) Internal KPI Synchronization Framework, and (3) Real-Time Performance Dashboard. The SMART evaluation determined the first alternative as the most effective, with the highest score (4.3), based on impact, feasibility, and ROI. The solution includes digital training, promotional kits, and incentive systems to enhance cashier performance. Supporting frameworks and monitoring systems were also proposed to ensure sustainable impact. The findings emphasize the importance of data-driven decision making, internal alignment, and proactive merchant involvement to enhance the success of banking partnership programs. This study contributes to strategic decision-making literature in the financial services sector by demonstrating the effective integration of KT and SMART to resolve operational inefficiencies.  Keywords: Kepner-Tregoe, SMART Technique, Credit Card Partnership, Decision Analysis, Banking Strategy
The Role of Artificial Intelligence–Based Decision Support Systems in Managerial Decision-Making in the Hospitality Industry: A Systematic Literature Review Gultom, Rafly Aqsha; Mustofa, Firzainy Jiddan; Tanaga, Selwin Malta
Community Engagement and Emergence Journal (CEEJ) Vol. 7 No. 3 (2026): Community Engagement & Emergence Journal (CEEJ)
Publisher : Yayasan Riset dan Pengembangan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/ceej.v7i3.10497

Abstract

The advancement of Artificial Intelligence (AI) has accelerated the adoption of Decision Support Systems (DSS) to assist managerial decision-making in the increasingly complex and dynamic hospitality industry. This study aims to systematically examine how AI-based DSS are utilized to support managerial decision-making in the hospitality sector, with a particular focus on the types of decisions supported, the AI techniques employed, the benefits obtained, and the challenges of implementation. This research adopts a Systematic Literature Review (SLR) approach guided by the PRISMA framework. A comprehensive literature search was conducted using the Scopus database, resulting in 32 peer-reviewed journal articles that met the inclusion criteria within the publication period of 2017–2026. The findings indicate that AI-based DSS are predominantly used to support operational and tactical decisions, particularly in demand and occupancy forecasting, dynamic pricing and revenue management, workforce scheduling, and service quality management. Machine learning and predictive analytics emerge as the most widely applied AI techniques, while rule-based systems are used to a more limited extent. The literature also highlights key benefits, including improved decision accuracy, enhanced operational efficiency, and better service quality. However, these benefits are accompanied by challenges related to data quality, system transparency, and organizational readiness. This study provides a structured synthesis of the role of AI-based DSS in managerial decision-making within the hospitality industry and offers a foundation for future research and managerial practice.
Co-Authors Mustofa, Firzainy Jiddan Siallagan, Manahan Parlindungan Sarigih Tanaga, Selwin Malta