Sistem Pendukung Keputusan Pemilihan Pemasok Kopi Menggunakan Metode AHP-TOPSIS (Studi Kasus: Perasa Coffee)

Abstract

The rapid growth of the coffee shop industry requires business owners to maintain their product quality, which heavily depends on the supply of roast beans. Perasa Coffee currently faces challenges in selecting suppliers because the evaluation process is still conventional, subjective, and lacks a systematic multi-criteria assessment. This condition leads to high risks of inconsistent coffee quality, lack of freshness, and delivery delays. Therefore, this research aims to build a web-based Decision Support System (DSS) using the Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods to provide objective and accurate supplier recommendations. This research used a quantitative applied approach by evaluating four supplier alternatives based on four main criteria: Price, Quality, Delivery Speed, and Service. The AHP method was utilized to calculate and determine the criteria weights. The calculation resulted in Quality as the highest priority criterion (54.2%), followed by Price (23.3%), Delivery Speed (13.9%), and Service (8.4%). The consistency test yielded a Consistency Ratio (CR) of 0.023, proving that the expert's judgments were consistent and valid. Furthermore, the TOPSIS method ranked the alternatives based on their distances to the ideal solutions. The mathematical result showed that Roastery Delta (A4) was selected as the best supplier with the highest preference value of 0.626. In conclusion, the integration of AHP and TOPSIS algorithms into a web-based DSS successfully optimized the supplier selection process at Perasa Coffee, ensuring the decision-making is efficient, mathematically accurate, and free from human subjectivity.