Analysis of the Simple Additive Weighting and Similarity Methods in Decision Support Systems for SDLC Method Selection - Ryci Rahmatil Fiska; Muhammad Asyraf Pratama (SISTEMASI, 2026)
Selecting an appropriate Software Development Life Cycle (SDLC) method is a critical factor in the success of software development projects. However, the selection process is often conducted subjectively without in-depth analysis of project characteristics. This study aims to analyze the comparison between the pure Simple Additive Weighting (SAW) method and SAW combined with the similarity method in a decision support system for SDLC method selection. The study utilized 14 SDLC method alternatives and 9 evaluation criteria, including estimated project duration, risk level, system complexity, budget, team size, team experience level, user involvement, changing requirements, and documentation needs. The calculation results show that the pure SAW method recommended DevOps with a score of 84.07%, while the SAW method combined with similarity recommended Test-Driven Development (TDD) with a score of 99.63%, representing an increase of 15.56 percentage points. Ranking changes occurred in 13 out of the 14 methods evaluated, with 7 methods experiencing rank increases and 6 methods experiencing rank decreases. The similarity-based approach proved to generate recommendations that are more aligned with project characteristics because it considers the level of similarity between the project profile and the characteristics of each SDLC method.