Integrasi Fuzzy Sugeno & Fuzzy Tsukamoto untuk Readiness Deployment Aplikasi Perbankan berbasis dokumen checklist QA - Noka Prakasa Rhomadona; Luqman (Jurnal E-Komtek, 2026)
This research proposes a decision support expert system for the readiness deployment process based on a QA checklist by integrating the Fuzzy Tsukamoto and Fuzzy Sugeno methods. This research is very necessary because application release failures to production still often occur due to inconsistent testing and reliance on the experience of Quality Assurance (QA), especially in the workplace of the researcher. The variables used for analysis are five, namely error handling, multi-platform testing, performance testing, defect handling, and UAT results. Fuzzification is mapped into 3 categories: LOW/MEDIUM/HIGH, which is implemented using a trapezoid function; Tsukamoto output is in the form of a monotonous curve shaped L/R (rising or falling). Sugeno uses constants or linear functions. In this study, an internal dataset was used with a total of 500 data points, with 185 ready data, 220 partially ready data, and 95 not ready data. I performed numerical mapping on the fuzzification categories [LOW, MEDIUM, HIGH] as [0,30, 0,60, 0,90], for a weight λ of 0.70 and showed an accuracy of 83.8%. This system provides consistent recommendations and conservative safeguards against critical conditions before production release.