Implementasi Metode SAW Dan MAUT Dalam Sistem Pendukung Keputusan Menentukan Verietas Nanas Terbaik - Rahmad Aditiya; Angga Putra Juledi; Kusmanto; Andi Ernawari; Muhammad Bobbi Kurniawan Nasution (Forum Kerjasama Pendidikan Tinggi (FKPT), 2026)
This research aims to assist farmers and agribusiness practitioners in determining the best pineapple variety in a more objective and systematic manner. Ultimately, this will positively impact the productivity and quality of pineapple yields, providing greater economic benefits to farmers and agribusiness practitioners. To address this issue, a Decision Support System (DSS) was employed using the SAW and MAUT methods. The SAW method is a simple and easily implemented MCDM method. It works by assigning weights to each criterion and then calculating the total score for each alternative based on these weights. On the other hand, the MAUT method is a more comprehensive approach to multi-criteria decision-making. This method is based on utility theory, which considers the decision-maker's preferences regarding various attributes or criteria. By using the SAW and MAUT methods, we can determine the best pineapple variety selection based on the available data. From the previously collected data, this study uses 5 criteria: Size (30%), Taste (25%), Skin Color (20%), Water Content (15%), and Texture (10%). The implementation of the SAW and MAUT methods revealed that the best pineapple variety is A5 (MD2) with a score of 0.9125 using the SAW method and a score of 2.2062 using the MAUT method. The last-ranked alternative, A10, shared the same ranking.