ITEM ANALYSIS OF BUFFER SOLUTION MULTIPLE-CHOICE TEST

Authors

  • Kiky Setiawan Sekolah Menengah Kejuruan 1 Sidoarjo, Indonesia
  • Rufi'i Universitas PGRI Adi Buana Surabaya, Indonesia
  • Sabariah Universitas PGRI Adi Buana Surabaya, Indonesia

DOI:

https://doi.org/10.23969/jp.v11i02.47117

Keywords:

item analysis, classroom assessment, multiple-choice test, test reliability, buffer solution

Abstract

This study evaluated the quality of an end-of-chapter multiple-choice test on buffer solution material by examining reliability, item difficulty, discrimination, and distractor effectiveness. A descriptive quantitative design based on classical test theory was used. The data consisted of responses from 35 students to 25 multiple-choice items and were analyzed using ANATES. The results showed a reliability coefficient of 0.72, indicating acceptable overall consistency. However, all items were categorized as very easy, with correct response rates ranging from 88.57% to 100%. Discrimination analysis showed that 17 items were poor, 5 were moderate, 2 were good, and 1 was very good. Distractor analysis also indicated that most incorrect options were non-functional because they were rarely or never selected. Only items 2, 7, and 23 were recommended for retention without revision, while most items required revision or removal. These findings indicate that total-score reliability alone is insufficient for judging assessment quality. Routine item analysis is therefore essential to strengthen the diagnostic usefulness of chemistry classroom assessment.

Downloads

Download data is not yet available.

References

Alenezi, dkk. (2024). Item analysis: the impact of distractor efficiency on the difficulty index and discrimination power of multiple-choice items. BMC Medical Education

Allahverdipour, H., Badri, M., Shaghaghi, A., Mahmoodi, H., Heizomi, H., Shirzadi, S., & Jafarabadi, M. A. (2023). Medications Non-Adherence Reasoning Scale (MedNARS): Development and psychometric properties appraisal. Health Promotion Perspectives, 13(3), 212-218. https://doi.org/10.34172/hpp.2023.26

Butz, A. R., & Branchaw, J. (2020). Entering Research Learning Assessment (ERLA): Validity evidence for an instrument to measure undergraduate and graduate research trainee development. CBE-Life Sciences Education, 19(2), ar18. https://doi.org/10.1187/cbe.19-07-0146

Chauhan, G. R., et al. (2023). Relations of the Number of Functioning Distractors With the Item Difficulty Index and the Item Discrimination Power in the Multiple Choice Questions. Cureus. DOI: https://doi.org/10.7759/cureus.42492

DeCarlo, L. T. (2023). Classical Item Analysis from a Signal Detection Perspective. Journal of Educational Measurement, 60(3), 520–547. https://doi.org/10.1111/jedm.12358

Donnelly, J. P., Finn, K. E., & Stewart, A. D. (2023). Development of a brief college embeddedness scale. Journal of College Student Retention: Research, Theory & Practice, 27(4), 995-1010. https://doi.org/10.1177/15210251231217094

Hermanto, F. Y., Anggraeni, A. D., & Sutirman. (2025). Analisis Butir Soal dengan Classical Test Theory untuk Mengukur Kemampuan Kognitif Siswa. Efisiensi: Kajian Ilmu Administrasi. https://doi.org/10.21831/efisiensi.v20i2.80225

Kubo, S. (2023). Test Theory Underpinning Learner Assessment. Journal of the Japan Society for Medical Education, 54(4), 367–375. https://doi.org/10.11307/mededjapan.54.4_367

Nurjanah, S., Iqbal, M., Zafrullah, Z., Mahmud, M. N., Seran, D. S. F., Suardi, I. K., & Arriza, L. (2024). Psychometric quality of multiple-choice tests under classical test theory (CTT): AnBuso, Iteman, and R. Jurnal Penelitian dan Evaluasi Pendidikan, 28(2), 161–172. https://doi.org/10.21831/pep.v28i2.71542

Priyani, T., & Sugiharto, B. (2024). Analysis of biology midterm exam items using a comparison of the classical theory test and the Rasch model. Jurnal Pendidikan Biologi Indonesia. DOI: https://doi.org/10.22219/jpbi.v10i3.34345

Slepkov, A. D., Bussel, M. L. V., Fitze, K. M., & Burr, W. S. (2021). A baseline for multiple choice testing in the university classroom. SAGE Open, 11(2). https://doi.org/10.1177/21582440211016838

Syamsuddin, Syaiful Syamsuddin (2023). Implementasi Classic Test dan Item Response Theory Pada Penilaian Tes Pembelajaran Matematika. EDUSCOPE: Jurnal Pendidikan, Pembelajaran, dan Teknologi. https://doi.org/10.32764/eduscope.v8i2.3488

Yulisharyasti, L., Nurdin, A., Aulia, N., Arfa, F. A. H., & Fadjryani. (2023). Analyzing the Quality of Measurement Instruments of Multiple Choice Questions through Classical Test Theory and Rasch Models. https://doi.org/10.22487/27765660.2023.v3.i1.16417

Zakiyah, Z., & Hidayah, A. (2023). The COVID-19 pandemic and the characteristic comparison of English achievement tests. Perspectives of Science and Education, 62(2), 307-329. https://doi.org/10.32744/pse.2023.2.18

Downloads

Published

2026-06-30