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Journal : TECHNOVATE

Implementation of Profile Matching Method for E-Wallet Selection Recommendations in Indonesia Pratistha, Indra; Widiari, Ni Putu Diva Septa; Dewi, Ni Luh Putu Berliana; Jaya, I Made Krisna; Sudipa, I Gede Iwan
TECHNOVATE: Journal of Information Technology and Strategic Innovation Management Vol. 2 No. 3 (2025): July 2025
Publisher : PT.KARYA GEMAH RIPAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52432/technovate.2.3.2025.112-122

Abstract

The development of e-wallet adoption in Indonesia accompanied by a diversity of features and service quality triggers user confusion in determining the most suitable application. This study develops a Decision Support System (SKS) to recommend the best e-wallet objectively. Using Profile Matching, the research compares the actual profile of each e-wallet against the ideal profile based on 5 criteria and 15 sub-criteria. Data obtained from 30 respondents. The process includes GAP mapping, weight conversion, Core Factor-Secondary Factor clustering, total value calculation per criteria, and then weighted aggregation for ranking. The final recommendation places DANA as the best alternative (3.86), followed by GoPay (3.80) and OVO (3.72). These results show that Profile Matching effectively handles multi-criteria decision-making in the consumer fintech space and provides consistent, transparent and replicable evaluation. The findings provide practical benefits for users in choosing an e-wallet as well as academic contributions in the form of structured application of decision-making methods in the context of digital payments. Further research is recommended to expand the sample, add criteria (cost, customer service, privacy), conduct a test of comparison methods, perform sensitivity tests, and integrate behavioral data to improve external validity and accuracy of recommendations.
A Profile Matching-Based Decision Support Framework for Selecting Generative AI Tools in Higher Education Pratistha, Indra; Anggaswara, Aditha Diva; Saputra, Gusti Bagus Arya; Krisna, I Gede Anugrah Adi; Sudipa, I Gede Iwan
TECHNOVATE: Journal of Information Technology and Strategic Innovation Management Vol. 3 No. 1 (2026): January - February 2026
Publisher : PT.KARYA GEMAH RIPAH

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to develop a decision-making model for determining the best AI application, specifically for students, in selecting the best alternative based on various criteria. This study used the Profile Matching Method to rank alternatives. Data was collected from students through an online survey, with criteria including ease of use (C1), task completion support (C2), creativity and idea support (C3), output quality and accuracy (C4), flexibility of use (C5), and access cost (C6). A decision-making analysis was conducted to determine the application that best suited students' preferences and identified the factors that most influenced their choice. The results showed the ChatGPT application alternative (A1) as the best student choice.