Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika
Praharto, Suwandhy
Unknown Affiliation
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Implementing TOGAF Enterprise Architec-ture in Indonesia’s Merchant Acquiring In-dustry: A Framework for Digital Trans-formation Praharto, Suwandhy; Yohanis, Alfa Ryano
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 2 (2025): Research Articles April 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i2.14668

Abstract

The digital transformation of Indonesia's merchant-acquiring industry, accelerated by regulatory initiatives, fintech innovations, and changing consumer behavior, has created significant technological and organizational challenges. Fragmented legacy systems and complex regulatory requirements hinder seamless digital payment adoption. This study investigates the strategic implementation of The Open Group Architecture Framework (TOGAF) to systematically manage these challenges. Through an extensive literature review and case studies of major industry players—including BRI, BCA, Mandiri, BNI, and GoPay—this research uniquely explores TOGAF's specific applicability to merchant acquiring in Indonesia. The proposed TOGAF-based framework aligns closely with Bank Indonesia's Payment System Blueprint 2025, emphasizing enhanced interoperability, regulatory compliance, and sustainable growth. Findings suggest that enterprise architecture can unify fragmented technologies, bridge gaps in merchant activation, and strengthen cybersecurity, ultimately driving innovation in digital payment services. By providing a structured implementation roadmap tailored to Indonesia's regulatory environment, this research not only addresses current industry needs but also sets a foundation for future technological advancement and financial inclusion in Indonesia's merchant acquiring landscape.
Data Mining Framework for EDC Terminal Repair Protocol: Combining Apriori and PrefixSpan Praharto, Suwandhy; Santoso, Handri
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 2 (2025): Research Articles April 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i2.14759

Abstract

Electronic Data Capture (EDC) terminals are vital for financial transactions, but their repair processes often lack standardization, causing inefficiencies. Data mining techniques like Association Rule Mining (ARM) and Sequential Pattern Mining (SPM) can extract hidden patterns from service logs to inform maintenance strategies. This research addresses the limited use of these techniques within Electronic Data Capture (EDC) repair centers. Specifically, it applies Association Rule Mining (ARM) using the Apriori algorithm, and Sequential Pattern Mining (SPM) using the PrefixSpan algorithm, to optimize repair protocols based on historical repair data from PT. XYZ Indonesia. The study aimed to discover frequent fault-action-component associations and repair sequences to formulate standardized procedures. A quantitative case study analyzed 56,629 repair transactions. After data cleaning and transformation, Apriori (evaluated by support, confidence, lift) mined association rules, while PrefixSpan found frequent sequential patterns (evaluated by minimum support). Several high-confidence rules emerged: "Battery Not Charging" almost always led to "Replace Battery Pack" (≈95% confidence, lift ≈6.0), and error "2000000" (tamper indication) strongly correlated with detampering procedures and internal battery replacement (≈96% confidence, lift ≈4.9). PrefixSpan uncovered consistent repair sequences, including length-3 patterns for complex issues, with "Replace CMOS → Reinstall OS" for error "7FFFFF" being a prominent shorter sequence. Integrating these data-driven patterns into protocols and aligning inventory can improve service efficiency, reduce repair time, and enhance EDC reliability.
Co-Authors Santoso, Handri Yohanis, Alfa Ryano