Email this article Evaluation of Accreditation and National Examination using Multilevel Generalized Structured Component Analysis
Abstract
Abstract: Evaluation of Accreditation and National Examination using Multilevel Generalized Structured Component Analysis. Hierarchical elements or higher levels often influence school accreditation and the national exam because education units are nested in the characteristics of the province. Objectives: This study aims to evaluate the relationship between accreditation and the national exam at the level of Junior high school/Madrasa in Java which are nested in province. Methods: The analysis employs multilevel GSCA analysis (MGSCA). Findings: UNBK has good convergent validity and it can explain each of the subjects tested in each province up to more than 90 percent. Concerning the estimates of path coefficients, the study found eight patterns of relationship between SNP and UNBK that have a significant effect in the six provinces. Conclusion: The relationship between content and competency standard for UNBK shows that there are significant differences in all provinces in Java island. This shows that provincial characteristics affect school quality. The model can explain the total variability of all variables is 72.44 percent.
Keywords: multilevel generalized structured component analysis, national education standards, national examination.
Abstrak: Evaluasi Akreditasi dan Ujian Nasional menggunakan Analisis Komponen Terstruktur Umum Bertingkat. Unsur berhierarki atau tingkat yang lebih tinggi sering mempengaruhi akreditasi dan ujian nasional karena satuan pendidikan bersarang di karakteristik provinsi. Unsur hierarki atau jenjang yang lebih tinggi seringkali mempengaruhi akreditasi sekolah dan ujian nasional karena satuan pendidikan bersarang pada karakteristik provinsi. Tujuan: Penelitian ini bertujuan untuk mengevaluasi hubungan antara akreditasi dengan ujian nasional pada tingkat SMP/Madrasah di Jawa yang bersarang di provinsi. Metode: Analisis menggunakan analisis GSCA bertingkat (MGSCA). Temuan: UNBK memiliki validitas konvergen yang baik dan dapat menjelaskan setiap mata pelajaran yang diujikan di setiap provinsi hingga lebih dari 90 persen. Mengenai estimasi koefisien jalur, studi menemukan delapan pola hubungan antara SNP dan UNBK yang berpengaruh signifikan di enam provinsi. Kesimpulan: Hubungan antara isi dan standar kompetensi UNBK menunjukkan adanya perbedaan yang signifikan di semua provinsi di pulau Jawa. Hal ini menunjukkan bahwa karakteristik provinsi mempengaruhi kualitas sekolah. Model tersebut dapat menjelaskan total variabilitas semua variabel sebesar 72,44 persen.
Kata kunci: analisis komponen terstruktur umum bertingkat, standar nasional pendidikan, ujian nasional.
Full Text:
PDFReferences
Astivia, O. L. O., & Zumbo, B. D. (2019). Heteroskedasticity in Multiple Regression Analysis: What it is, How to Detect it and How to Solve it with Applications in R and SPSS. Practical Assessment, Research, and Evaluation, 24(1), 1.
Audigier, V., White, I. R., Jolani, S., Debray, T. P. A., Quartagno, M., Carpenter, J., van Buuren, S., & Resche-Rigon, M. (2018). Multiple imputation for multilevel data with continuous and binary variables. Statistical Science, 33(2), 160–183.
Crockett, S. A. (2012). A five-step guide to conducting SEM analysis in counseling research. Counseling Outcome Research and Evaluation, 3(1), 30–47.
Hair, J. F. (2021). Reflections on SEM: An Introspective, Idiosyncratic Journey to Composite-based Structural Equation Modeling. ACM SIGMIS Database: The DATABASE for Advances in Information Systems, 52(SI), 101–113.
Henseler, J. (2017). Bridging design and behavioral research with variance-based structural equation modeling. Journal of Advertising, 46(1), 178–192.
Hijrah, M., Susetyo, B., & Sartono, B. (2018). Structural equation modeling of national standard education of vocational high school using partial least square path modeling. International Journal of Scientific Research in Science Engineering and Technology, 4(4), 1418–1422.
Hwang, H., Sarstedt, M., Cheah, J. H., & Ringle, C. M. (2020). A concept analysis of methodological research on composite-based structural equation modeling: bridging PLSPM and GSCA. Behaviormetrika, 47(1), 219–241.
Hwang, H., & Takane, Y. (2014). Generalized structured component analysis: A component-based approach to structural equation modeling. CRC Press.
Hwang, H., Takane, Y., & Malhotra, N. (2007). Multilevel generalized structured component analysis. Behaviormetrika, 34(2), 95–109.
Leckie, G., French, R., Charlton, C., & Browne, W. (2014). Modeling heterogeneous variance–covariance components in two-level models. Journal of Educational and Behavioral Statistics, 39(5), 307–332.
Moore, Z., Harrison, D. E., & Hair, J. (2021). Data Quality Assurance Begins Before Data Collection and Never Ends: What Marketing Researchers Absolutely Need to Remember. International Journal of Market Research, 63(6), 693–714.
Purwanto, A., & Sudargini, Y. (2021). Partial Least Squares Structural Squation Modeling (PLS-SEM) Analysis for Social and Management Research: A Literature Review. Journal of Industrial Engineering & Management Research, 2(4), 114–123.
Ryoo, J. H., & Hwang, H. (2017). Model evaluation in generalized structured component analysis using confirmatory tetrad analysis. Frontiers in Psychology, 8, 916.
Ryoo, J. H., Park, S., Kim, S., & Ryoo, H. S. (2020). Efficiency of cluster validity indexes in fuzzy clusterwise generalized structured component analysis. Symmetry, 12(9), 1514.
Setiawan, A. I., Susetyo, B., & Fitrianto, A. (2018). Application of generalized structural component analysis to identify relation between accreditation and national assessment. International Journal of Scientific Research in Science Engineering and Technology, 4(10), 93–97.
Suk, H. W., & Hwang, H. (2016). Functional generalized structured component analysis. Psychometrika, 81(4), 940–968.
Susetyo, B., & Wahyuni, R. (2021). Application of the fuzzy clusterwise generalized structured component method to evaluate implementation of national education standard in Indonesia. Management Science Letters, 11(4), 1379–1384.
Vita, F., Susetyo, B., & Indriyanto, B. (2015). Generalized structured component analysis for national education standards of secondary school in Indonesia. Global Journal of Pure and Applied Mathematics, 11(4), 2441–2449.
Wu, W., Carroll, I. A., & Chen, P.-Y. (2018). A single-level random-effects cross-lagged panel model for longitudinal mediation analysis. Behavior Research Methods, 50(5), 2111–2124.
Zhu, C., Lopez, R. A., & Liu, X. (2016). Information cost and consumer choices of healthy foods. American Journal of Agricultural Economics, 98(1), 41–53.
Refbacks
- There are currently no refbacks.
Copyright (c) 2022 Jurnal Pendidikan Progresif
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
View My Stats
The copyright is reserved to The Jurnal Pendidikan Progresif that is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.