Data-Based Fuzzy TOPSIS for Alternative Ranking
Abstract: Technique for
order preference by
similarity (TOPSIS) solves
multi-criteria decision making
(MCDM) by ranking
the alternatives. When the
attributes are not
deterministic, a Fuzzy
TOPSIS method is
applied. The traditional
fuzzy TOPSIS depends on decision
makers to determine alternative’s value which considered subjective. A new
method named data-based fuzzy
TOPSIS proposed to
diminish the dependency
to decision maker.
The proposed algorithm
use data to
determine alternative’s values objectively. Subtractive Clustering (SC)
and Fuzzy C-Mean (FCM) selected to transform crisp value data to fuzzy value
data. Some modification applied to SC and FCM to obtain fuzzy triangular value
needed by fuzzy TOPSIS.
Author: Victor Utomo, Rachmat
Gernowo
Jounal Code: jptinformatikagg130004
