<![CDATA[This study develops a Decision Support System (DSS) for employee loans using the Simple Additive Weighting (SAW) method. The main issue addressed is the need for an efficient and objective selection process for prioritizing loan applications in an employee cooperative. The system aims to assist loan managers in selecting the most qualified applicants by calculating a preference score based on predefined criteria. These criteria include membership status, urgency of the loan, submission order, income level, and outstanding previous loans. The SAW method was chosen due to its effectiveness in ranking multiple alternatives by weighting criteria and normalizing decision matrices. The system processes data from cooperative members and generates a preference score that highlights which applicants should be prioritized for loan approval. The results show that the system successfully prioritizes applicants, with Akhirudin being the top recommendation (0.925), followed by Agus Mulyanto (0.8375) and Yuharmen (0.7965). Conversely, Riza Puspita was ranked last (0.408) due to a lower urgency and income level. This study concludes that the DSS based on SAW provides an accurate, transparent, and efficient solution for loan approval decision-making.]]>
Copyrights © 2023
