Implementation of Fuzzy Possibilistic C-Means with Optimal Membership of Fuzzy C-Means for Stunting Management in Central Java Province
Year: 2025
Type: article
Abstract: Stunting is a serious problem makes children vulnerable disease and reduced productivity. According to Indonesian Health Survey (2023), stunting rate Indonesia in 2023 was 21.5%. The target set in 2020-2024 National Medium-Term Development Plan of 14% and WHO standard below 20% have still not been achieved. Based on Indonesian Health Survey (2023), prevalence stunting in Central Java Province in 2023 has decreased only 0.1% to 20.7%. Therefore, it is necessary to evaluate acceleration stunting handling from achievement more focused and targeted Special Index for Stunting Management (IKPS) indicators, one of which is through clustering analysis. The data used is the indicators IKPS of districts/cities in Central Java Province from the official website of the Central Bureau of Statistics (BPS) in 2023. The data contains outliers because the acceleration rate of stunting reduction varies in each region. Fuzzy Possibilistic C-Means algorithm with optimal membership of Fuzzy C-Means which is able to handle outlier data, is used in this research. The clustering results using the algorithm will be validated using the Davies Bouldin Index (DBI) to find the most optimal cluster. The validated shows the optimal cluster with 5 clusters and a DBI value of 1.520291.
Institution: Diponegoro University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4410922778