The Fuzzy-Possibilistic Product Partition c-Means (FPPPCM) algorithm for Clustering the Welfare Levels of Regencies in East Java

Amanatullah Pandu Zenklinov; Alicia Arifin

doi:10.20956/j.v21i3.43339

Authors

Amanatullah Pandu Zenklinov Matana University
Alicia Arifin Matana Unversity

DOI:

https://doi.org/10.20956/j.v21i3.43339

Keywords:

Clustering, FPPPCM, Welfare

Abstract

Welfare is a condition where society is free from deviant behavior, poverty, ignorance, and fear, thus allowing individuals to obtain a safe and peaceful life. East Java is among the provinces in Indonesia that recorded the highest incidence of poverty from 2013 to 2022; however, it has also demonstrated a consistent decline in the number of individuals living in poverty during this period. This study aims at applying the Fuzzy-Possibilistic Product Partition c-Means (FPPPCM), which combines the probabilistic approach of Fuzzy c-Means and the possibilistic approach of Possibilistic c-Means, and is effective in handling outliers, to clustering the welfare levels of regencies and cities in East Java. The exploration is based on the data of the Badan Pusat Statistik (BPS) for 2024. Based on clustering the welfare levels, the following are the end results of the study: Cluster 1 (low population, high education/life expectancy but low labor participation and high poverty line, i.e. Kediri City) may find aid in programs that work on the issues like job creation, affordable housing, and family planning outreach to reduce inequality. Cluster 2 (medium population, low education/expenditure but high labor participation/home ownership, i.e. Pacitan) could promote vocational training, poverty reduction through SME support, and give education to the workforce. Cluster 3 (high population, low life expectancy, medium indicators but high family planning, i.e. Lamongan) should focus on improvement of the healthcare infrastructure, the health of the mother and child, and creation of industrial jobs for the local people

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