FUZZY MAMDANI EXPERT SYSTEM FOR PROPERNESS OF SELECTING SUPPLIER IN CORPORATE XYZ - Hendriyanto, Hendriyanto; Irawan, Bei Harira; Prihadi, Deddy; Hartati, Indah (Asia Information System Journal, 2023)
This research aims to enhance the supplier selection process at Corporate XYZ by implementing the Fuzzy Mamdani Expert System, which addresses the complexities of evaluating suppliers in a service-oriented business environment. The study employs a fuzzy logic approach to assess suppliers based on multiple qualitative and quantitative criteria, including cost efficiency, reliability, and scalability. The methodology involves fuzzification of input data, rule base evaluation, and the application of the Mamdani inference system to derive crisp scores for each supplier. The findings indicate that Supplier A scored 85 points, outperforming Supplier B, which scored 70 points, highlighting the effectiveness of the evaluation process. Additionally, the research identifies potential risks associated with suppliers, such as pending legal documentation, which could impact their overall scores. The conclusion emphasizes that the Fuzzy Mamdani Expert System not only facilitates informed decision-making in supplier selection but also fosters continuous improvement through a feedback loop mechanism. This study contributes to the field of supply chain management by demonstrating the applicability of fuzzy logic in optimizing supplier evaluations, ultimately leading to better supplier relationships and cost efficiencies for organizations. Future research is suggested to explore the integration of additional criteria and advanced analytical techniques.