LEVERAGING THE SAW METHOD IN A DECISION SUPPORT SYSTEM TO IMPROVE ELDERLY NUTRITION AT LAWEYAN HOME FOR THE ELDERLY

Abstract

This community engagement initiative addresses nutritional challenges among elderly residents at the Laweyan Home for the Elderly in Surakarta by developing a Decision Support System (DSS) utilizing the Simple Additive Weighting (SAW) method. The DSS was designed to assist caregivers in making informed meal selections based on individualized health profiles, including demographic data, medical conditions, and allergy history. Implemented as a web-based application, the system enables users to input resident data and receive prioritized dietary recommendations aligned with established nutritional criteria. The SAW algorithm processes multi-criteria input to rank food alternatives effectively. Empirical validation using real-world data demonstrated the system's capacity to generate accurate, personalized suggestions that support improved nutritional outcomes. Additionally, caregiver training and participatory implementation ensured practical usability and sustainability. This project highlights the potential of integrating algorithmic decision-making with community-based care to enhance the quality of elderly nutrition management in institutional settings.