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Clustering ECE and NFE Accredited Statuses with Unsupervised Possibilistic Fuzzy C-Means Prihantoro, Agung; Kartianom, Kartianom; Atymtaevna, Begimbetova Guldana
Nuansa Akademik: Jurnal Pembangunan Masyarakat Vol. 10 No. 2 (2025): In Progress
Publisher : Lembaga Dakwah dan Pembangunan Masyarakat Universitas Cokroaminoto Yogyakarta (LDPM UCY)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47200/jnajpm.v10i2.3025

Abstract

The research aims to have clusters of accredited statuses of early childhood education (ECE) and non-formal education (NFE) institutions in Yogyakarta Special Province in Indonesia, which are created by unsupervised possibilistic fuzzy c-means (UPFC) and to organize the institutions into the clusters created. The Board of National Accreditation for ECE and NFE determined four accredited statuses of A, B, C, and TT. The research employs a method of machine learning, especially UPFC. The dataset is a data of accreditation 2022 from the Board of National Accreditation for ECE and NFE of Yogyakarta Special Province. The data consists of 760 institutions composed of 749 (98.55%) ECE institutions and 11 (1.45%) NFE institutions. The analysis of UPFC created two clusters of accredited statuses of the institutions, thar are Accredited A that consists 437 (57.5%) institutions and Accredited B consisting of 323 (42.5%) institutions. The names of the clusters have political impact.