Application of the fuzzy clusterwise generalized structured component method to evaluate implementation of national education standard in Indonesia

Abstract

Article history: Received: July 10, 2020 Received in revised format: October 18 2020 Accepted: November 4, 2020 Available online: November 4, 2020 Results of school accreditation and national examinations are two indicators that are often used to describe the achievement of quality in education in Indonesia. ‘Accreditation’ reflects the fulfillment of 8 national education standards (NES), while the national exam (NE, or UN in Bahasa) for students describes academic performance. Eight NES and academic performance are latent variables. The relationship between the two variables and the validity of its indicators can be evaluated by several methods. Path analysis with latent variables can be obtained through general structured component analysis (GSCA) with the assumption of homogeneity of variance. Since the data are not homogeneous, this study aims to apply the fuzzy clusterwise generalized structured component analysis (FCGSCA) to evaluate the relationship between the NES and the UN, and the validity of the indicators. The results showed that there were two school clusters in Indonesia. The evaluation of the measurement model indicated that some indicators of the accreditation instrument were not valid, i.e., 6 indicators in cluster 1 and 15 indicators in cluster 2. The structural model evaluation of the two clusters indicated that standard of process to the UN was not significant. Based on the overall goodness of the fit model, the total diversities of all variables that could be explained were 61.60% in cluster 1 and 59.90% in cluster 2. © 2021 by the authors; licensee Growing Science, Canada