Page 58 - 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
COMPARISON OF FUZZY C-MEANS, FUZZY
POSSIBILISTIC C-MEANS AND POSSIBILISTIC
FUZZY C-MEANS ALGORITHMS ON THE
DISTRIBUTION OF CONTRACEPTIVE USERS IN NTB
PROVINCE

1
1
2*
Laily Rizqi Amaliyah , Abdul Rahim , Ayu Septiani

1 Department of Statistics, Universitas Hamzanwadi
(INDONESIA)
2 Departement Of Pharmacy, Universitas Mulawarman
(INDONESIA)

*Corresponding author: rahimkhanrewa12@gmail.com

Abstract
Fuzzy Clustering is one of the parts from purposeful cluster method
for group data by similarity characteristics. Advantages from method
Fuzzy Clustering compared with method cluster other could make
more detailed clusters. There are several methods in Fuzzy
Clustering, including Fuzzy C-Means, Fuzzy Possibilistic C-Means
and Possibilistic Fuzzy C-Means. Third method the could applied in
various one field-field health that is for see scatter group user
contraception. Contraception is tool for prevent proclaimed pregnancy
for the success of the Family program Planning (KB) in push rate
growth resident. Destination from study this is for compare third
method Fuzzy Clustering with see score accuracy and see results
cluster best formed based on score index validity Modified Partition
Coefficient (MPC). Analysis result show that method Fuzzy C-Means
is the best method seen from more MPC value height in each cluster.
However, if seen from score iteration and time computation, method
Fuzzy Possibilistic C-Means far more effective. There are 2 optimal

ISST 2022 – FST Universitas Terbuka, Indonesia 37
International Seminar of Science and Technology “Accelerating Sustainable
Towards Society 5.0