A SAW-Based Multi-Criteria Approach for Selecting Strategic Café Branch Locations - Asih Anggina; Shary Armonitha Lusinia; Devia Kartika (PT. Teknologi Futuristik Indonesia, 2025)
The rapid development of information technology and artificial intelligence has increased the importance of data-driven decision-making, particularly in competitive industries such as cafés, where branch location significantly affects business success. However, selecting the optimal location remains a challenge due to the variability of local market conditions and the subjectivity of manual assessments, representing a gap in practical, objective evaluation methods. This study aims to determine the most suitable location for Anomali Café’s new branch in Padang City using the Simple Additive Weighting (SAW) method, a transparent and effective multi-criteria decision-making approach. The analysis of ten candidate sites reveals that Pantai Air Manis Street achieves the highest overall score, followed closely by Sitebal, Gajah Mada, Raya Lubuk Buaya, and Dr. Sutomo Streets, while the remaining locations are less competitive. These findings provide actionable, data-driven guidance for strategic branch expansion and demonstrate the applicability of SAW in tailoring location decisions to the café industry’s specific context.