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Clustering of High School Quality Using Fuzzy C-Means in the Special Region of Yogyakarta Province Ilmi, Lilin Rofiqatul; Haryanto; Sumunaringtyas, Maria
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 2, May 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i2.2187

Abstract

This research aims to reveal the results of clustering high school quality using fuzzy c-means in the Special Region of Yogyakarta Province. This research is quantitative and descriptive. Data collection was conducted through documentation. The research data are secondary data from the 2023 high school education report card. The sample consisted of 51 schools, which were determined using the proportional stratified random sampling. Data analysis was performed using the quantitative descriptive method and fuzzy c-means. The results of the study are clustering on the main indicator data producing three clusters: cluster 1 consists of 11 private schools accredited A and B, cluster 2 consists of 22 public and private schools accredited A, and cluster 3 consists of 18 schools accredited A, B, and C. Cluster 2 excels with the overall best performance, cluster 1 has moderate performance with several areas needing improvement, such as instructional leadership, the use of information technology for budget management, and inclusiveness, and cluster 3 shows the lowest performance, requiring significant attention and improvement in almost all aspects, especially literacy, numeracy, instructional leadership, and the use of information technology for budget management. Cluster 3, which had the lowest performance, showed an urgent need for improvement in almost all aspects.
A Cognitive Diagnostic Model Approach to Developing and Validating a Mathematics Literacy Instrument on Systems of Linear Equations Krismanto, Nugro; Rahayu , Wardani; Ridwan , Achmad; Sumunaringtyas, Maria
Journal of Educational Sciences Vol. 10 No. 3 (2026): Journal of Educational Sciences
Publisher : FKIP - Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/jes.10.3.p.656-667

Abstract

This study addresses the limited availability of mathematics literacy assessments that provide detailed cognitive diagnostic information at the junior secondary level. While most existing instruments focus on total achievement scores, few are systematically developed to diagnose specific cognitive attributes underlying students’ problem-solving processes. This study aimed to develop and validate a mathematics literacy instrument on Systems of Linear Equations in Two Variables using a Cognitive Diagnostic Model framework. The instrument was constructed in the form of complex multiple-choice items with partial credit scoring and explicitly linked to four cognitive attributes through a Q-matrix specification. The development process included needs analysis, expert validation, pilot testing with 200 students, and large-scale field testing with 960 eighth-grade students. Data were analyzed using the Generalized Deterministic Inputs, Noisy “And” Gate model to estimate students’ cognitive mastery profiles. The findings revealed that 28.54% of students mastered all four attributes, whereas 28.75% did not master any attribute, indicating substantial polarization in conceptual and procedural understanding. The instrument demonstrated satisfactory content validity and classification reliability. This study contributes a systematically developed, curriculum-aligned diagnostic tool that advances mathematics literacy assessment beyond conventional score-based measurement.