Page 63 - Proceeding The 2nd International Seminar of Science and Technology : Accelerating Sustainable Innovation Towards Society 5.0

nd
The 2 International Seminar of Science and Technology
“Accelerating Sustainable innovation towards Society 5.0”
ISST 2022 FST UT 2022
Universitas Terbuka
6. Fix t with Equation (6).
ik
-1
2
[∑ m ((X ij -V kj ) )] η-1
t = j=1 -1 (6)
ik
2
∑ n [∑ m ((X ij -V kj ) )] η-1
i=1 j=1

7. Check condition stop:
a. If | Pt – Pt-1 | < ε or t > Maxiter then stop
b. If no: t = t+1 then repeat step 4

2.5 Possibilistic Fuzzy C-Means
Possibilistic Fuzzy C-Means (PFCM) is method development from
Fuzzy Possibilistic C-Means [17]. Development method the conducted
with give degrees different interests among matrix peculiarity relatively
and matrix peculiarity absolute [18]. Step- step in algorithm PFCM that
is as following:
1. Enter the data (Xij ) to be grouped in the form of a matrix of size
nxm (n = number of data, p = number of variables).
2. Determine:
a. Number of clusters (c ≥ 2)
b. FCM weighting power (w > 1)
c. PCM weighting power (η > 1
d. Maximum iterations
e. Smallest error ( ε)
f. Initial iteration (t=1)
g. Initial objective function (P 0 = 0)
h. Weighting coefficient for relative specificity (a > 0)
i. Weighting coefficient for absolute uniqueness (a > 0)
j. Coefficient γ(K=1)
3. Call matrix peculiarity relatively (μ ) and the cluster center (V kj )
ik
in the final result FCM method for count matrix peculiarity
absolute which is in the form of a relative peculiarity matrix (tik)
with Equation (7).

42 ISST 2022 – FST Universitas Terbuka, Indonesia
International Seminar of Science and Technology “Accelerating Sustainable
Towards Society 5.0