Decision Support System For Choosing The Best Layer Chicken Breed Using The Simple Additive Weighting (SAW) Method In Pasawahan Village,Purwakarta Regency

Abstract

Selecting a laying-hen breed is a critical decision because breeds differ in egg productivity, feed efficiency, disease resistance, environmental adaptability, age at first lay, egg quality, and mortality. In Pasawahan Village, Purwakarta Regency, selection has largely relied on experience and informal recommendations, making the assessment subjective. This study develops a decision support system that produces an objective recommendation using the Simple Additive Weighting (SAW) method. Data were collected through observation, interviews with farmers, and literature review. The system was developed using the Waterfall model, designed with UML, implemented with Flutter and Dart, and supported by Supabase as the database. Five alternatives were evaluated against seven weighted criteria, normalized, and aggregated into preference scores. Lohmann Brown achieved the highest score (0.871667), followed by Hy-Line Brown (0.851667), Isa Brown (0.846667), White Leghorn (0.740000), and KUB chicken (0.643333). Black-box testing of authentication, data management, SAW calculation, ranking, and user management functions was successful. The system makes breed selection more transparent, consistent, and structured; nevertheless, the criteria weights and sub-criteria scales should be validated across a broader farming population.