<![CDATA[The rapid growth of the laundry business demands fast, precise, and transparent operational management. However, Mending Laundry, a multi-outlet business in Bogor Regency, faces operational bottlenecks due to conventional paper-based systems. These issues include vulnerability to transaction recording errors, lack of multi-branch real-time financial monitoring for owners, potential attendance manipulation, manual payroll calculations, and clothes accumulation caused by absent customer notifications. To address these fragmented challenges holistically, this study aims to design and implement a web-based Multi-Branch Laundry Management Information System integrating cashier PIN Point of Sale (POS), Face Recognition biometrics with Geolocation (GPS), automated payroll, profit/loss reporting, and WhatsApp Gateway (Fonnte API). Developed using the Agile Personal Extreme Programming (PXP) methodology, the system caters to single-developer dynamics through rapid iterations. Functional Black Box testing yielded a 100% success rate across 15 modules. Biometric face recognition achieved 96.67% accuracy under ambient lighting within a 50-meter GPS radius. User Acceptance Testing (UAT) evaluated with 7 key stakeholders produced a score of 90.10% (Mean = 4.51, SD = 0.49), categorizing the system as 'Highly Feasible' under the Technology Acceptance Model (TAM) and DeLone & McLean framework. This research contributes to software engineering practice by proving that PXP effectively delivers complex, multi-module enterprise systems for MSMEs.]]>
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