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Setyono, R. Puji, Sarno, R..  2018.  Vendor Track Record Selection Using Best Worst Method. 2018 International Seminar on Application for Technology of Information and Communication. :41–48.
Every company will largely depend on other companies. This will help unite a large business process. Risks that arise from other companies will affect the business performance of a company. Because of this, the right choice for suppliers is crucial. Each vendor has different characteristics. Everything is not always suitable basically the selection process is quite complex and risky. This has led to a new case study which has been studied for years by researchers known as Supplier Selection Problems. Selection of vendors with multi-criteria decision making has been widely studied over years ago. The Best Worst Method is a new science in Multi-Criteria Decision Making (MCDM) determination. In this research, taking case study at XYZ company is in Indonesia which is engaged in mining and industry. The research utilized the transaction data that have been recorded by the XYZ company and analyzed vendor valuation. The weighting of Best Worst Method is calculated based on vendor assessment result. The results show that XYZ company still focuses on Price as its key criteria.
Plachkov, Alex, Abielmona, Rami, Harb, Moufid, Falcon, Rafael, Inkpen, Diana, Groza, Voicu, Petriu, Emil.  2016.  Automatic Course of Action Generation Using Soft Data for Maritime Domain Awareness. Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion. :1071–1078.

Information Fusion (IF) systems have long exploited data provided by hard (physics-based) sensors with the aspiration of making sense of the environment they are monitoring. In recent times, the IF community has recognized the potential of utilizing data generated by people, also known as soft data. In this study, we demonstrate how course of action (CoA) generation, one of the key elements of Level 3 High-Level Information Fusion and a vital component for security and defense decision support systems, can be augmented using soft (human-derived) data for improved mission effectiveness. This conceptualization is validated through an elaborate experiment situated in the maritime world. To the best of the authors' knowledge, this is the first study to apply soft data to automatic CoA generation in the maritime domain.