A Fuzzy Topsis Multiple-Attribute Decision Making for Scholarship
  Selection
  As the education fees are becoming more expensive, more students apply for
scholarships. Consequently, hundreds and even thousands of applications need to
be handled by the sponsor. To solve the problems, some alternatives based on
several attributes (criteria) need to be selected. In order to make a decision
on such fuzzy problems, Fuzzy Multiple Attribute Decision Making (FMDAM) can be
applied. In this study, Unified Modeling Language (UML) in FMADM with TOPSIS
and Weighted Product (WP) methods is applied to select the candidates for
academic and non-academic scholarships at Universitas Islam Negeri Sunan
Kalijaga. Data used were a crisp and fuzzy data. The results show that TOPSIS
and Weighted Product FMADM methods can be used to select the most suitable
candidates to receive the scholarships since the preference values applied in
this method can show applicants with the highest eligibility
