Optimasi Pemilihan Jenis Kayu Berbasis Multi-Kriteria untuk Mendukung Keputusan pada Industri Furnitur Menggunakan Metode Simple Additive Weighting - Iwan Giri Waluyo; Savitri Savitri; Wiwit Kurniawan (Bulletin of Computer Science Research, 2026)
Selecting the right type of wood is a crucial factor in the furniture industry, as it directly impacts product quality, cost efficiency, and market value. Relying on subjective selection processes can lead to inconsistent decision-making. This study aims to develop a decision support system to optimize wood selection for Sumber Rejeki Mebel using the Simple Additive Weighting (SAW) method. The wood types evaluated include Teak, Merbau, Kamper Samarinda, Meranti, and Borneo, based on four criteria: color, texture, price, and availability. Criterion weights were determined through subjective assessment by an expert—the furniture business owner, who possesses extensive experience in raw material selection—and were subsequently applied during the normalization and ranking stages of the SAW method. Data analysis results indicate that Kamper Samarinda achieved the highest preference score (0.668), followed by Teak (0.653), Merbau (0.615), Meranti (0.610), and Borneo (0.605). Implemented using PHP and MySQL, the system facilitates a faster, more consistent, and transparent evaluation process compared to manual methods. Theoretically, this research demonstrates that the SAW method effectively integrates various material quality criteria into a simple, easily implementable multi-criteria decision-making model. Practically, the developed system supports more objective raw material selection, thereby offering the potential to enhance product quality and operational efficiency within the furniture industry.