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Mapping Quality Gaps of Islamic and Non-Islamic Kindergarten: A Systematic Literature Review Agung Prihantoro; Oscar Ndayizeye; Begimbetova Guldana Atymtaevna
Ulumuddin: Jurnal Ilmu-ilmu Keislaman Vol 16 No 1 (2026): Ulumuddin: Jurnal Ilmu-Ilmu Keislaman
Publisher : Universitas Cokroaminoto Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47200/ulumuddin.v16i1.3373

Abstract

Quality of Islamic and Non-Islamic kindergarten is a serious problem to solve immediately. But no research is done on mapping quality gaps of kindergarten in the world. This research mapped quality gaps of kindergarten in the whole world. Research method is systematic literature review. Results of the research reveals that quality gaps of kindergarten were mapped into seven categories. They are (1) learning opportunity, (2) accreditation instrument, (3) graduate competence, (4) learning process, (5) teacher and education personnel, (6) facilities, (7) parent involvement. There is no different categories among Islamic and non-Islamic kindergartens. These gaps spread around the world in America, Asia and Europe continents. No article presents the gaps in Africa and Australia continents and it bears little big questions.
Clustering ECE and NFE Accredited Statuses with Unsupervised Possibilistic Fuzzy C-Means Agung Prihantoro; Kartianom Kartianom; Begimbetova Guldana Atymtaevna
Nuansa Akademik: Jurnal Pembangunan Masyarakat Vol. 10 No. 2 (2025)
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.