ANALISIS KESULITAN DAN KESESUAIAN BUTIR SOAL TEKNIK DIGITAL ANALOG BERBASIS MODEL RASCH
Abstract
This study evaluates the quality of the Final Semester Examination instrument for the Digital and Analog Electronics course using content validity and Rasch analysis. The instrument comprised 15 multiple-choice items, validated by four experts and administered to 30 first-semester students. Expert judgment indicated strong content validity in terms of construct relevance, wording clarity, and content appropriateness, with Aiken’s V values ranging from 0.813 to 0.938. Rasch analysis showed a stable item difficulty structure, reflected by an item reliability of 0.94 and an item separation index of 4.11, indicating the instrument’s capacity to distinguish multiple levels of item difficulty. In contrast, person reliability (0.60) and a standard error of measurement of 2.35 suggest limited discrimination of student ability, likely due to the relatively homogeneous sample and suboptimal alignment between item difficulty and ability distribution. The Wright Map highlights mismatches between item difficulty and student ability, providing diagnostic evidence for improving item distribution and assessment design.
Penelitian ini mengevaluasi kualitas instrumen Ujian Akhir Semester mata kuliah Teknik Digital dan Analog melalui validitas isi dan analisis Rasch. Instrumen terdiri atas 15 butir soal pilihan ganda yang divalidasi oleh empat pakar dan diujikan kepada 30 mahasiswa semester awal. Hasil validasi ahli menunjukkan validitas isi yang kuat pada aspek relevansi konstruk, kejelasan redaksi, dan kesesuaian konten, dengan nilai Aiken’s V berkisar antara 0,813 – 0,938. Analisis Rasch menunjukkan struktur kesulitan butir yang stabil, ditunjukkan oleh reliabilitas item sebesar 0,94 dan item separation sebesar 4,11, yang mencerminkan kemampuan instrumen membedakan beberapa tingkat kesulitan. Namun, person reliability sebesar 0,60 dan SEM sebesar 2,35 mengindikasikan daya pembeda kemampuan mahasiswa yang masih terbatas, dipengaruhi oleh homogenitas sampel dan ketidaksejajaran tingkat kesulitan butir. Wright Map mengungkap ketidaksesuaian antara kesulitan butir dan kemampuan mahasiswa sebagai dasar perbaikan distribusi soal dan desain asesmen.
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Aiken, L. R. (1985). Three coefficients for analyzing the reliability and validity of ratings. Educational and Psychological Measurement.
American Educational Research Association (AERA), American Psychological Association (APA), & (NCME), N. C. on M. in E. (2014). f o r E d u c a t i o n a l a n d P s y c h o l o g i c a l Te s t i n g (Vol. 0000000000).
Bond, T., & Fox, C. (2015). Applying the Rasch Model: Fundamental Measurement in the Human Sciences, 3rd ed. Routledge.
Bond, T., Yan, Z., & Heene, M. (2020). Applying the Rasch model: Fundamental measurement in the human sciences (4th Editio). Routledge. https://doi.org/https://doi.org/10.4324/9780429030499
Boone, W. J. (2016). Rasch Analysis for Instrument Development: Why, When, and How? CBE—Life Sciences Education, 15(4), rm4. https://doi.org/10.1187/cbe.16-04-0148
Clark, L. A., & Watson, D. (2019). Constructing validity: New developments in creating objective measuring instruments. Psychological Assessment, 31(12), 1412.
DeVellis, R. F. (2017). Scale Development Theory and Applications (Fourth Edition). SAGE Publication, 4, 256.
Dong, Y., Xu, W., Huang, J., & Yann, K. (2025). Validating and refining a multi-dimensional scale for measuring AI literacy in education using the Rasch Model. Humanities and Social Sciences Communications, 12(1), 1–13.
Feng, Y., Qiao, Y., Zhao, X., & Li, J. (2019). Study on Sample Size of Candidates Oriented to Online Test. 2019 14th International Conference on Computer Science & Education (ICCSE), 1006–1010.
Fischer, G. H. (2006). Rasch modeling. In Encyclopedia of Statistics in Behavioral Science: Everitt Behavioral (pp. 1–9). wiley. https://doi.org/10.1002/0470013192.bsa540
Fitrah, M., Sofroniou, A., & Judijanto, L. (2024). Reliability and Separation Index Analysis of Mathematics Questions Integrated with the Cultural Architecture Framework Using the Rasch Model. Journal of Education and E-Learning Research, 11(3), 499–509.
Hsu, J. L., Sung, R.-J., Swarat, S. L., Gore, A. J., Kim, S., & Lo, S. M. (2024). Variations in Student Approaches to Problem Solving in Undergraduate Biology Education. CBE—Life Sciences Education, 23(2), ar12. https://doi.org/10.1187/cbe.23-02-0033
Jerosch-Herold, C., Chester, R., & Shepstone, L. (2017). Rasch model analysis gives new insights into the structural validity of the quickdash in patients with musculoskeletal shoulder pain. Journal of Orthopaedic and Sports Physical Therapy, 47(9), 664–672. https://doi.org/10.2519/jospt.2017.7288
Khine, M. S. (2020). Objective measurement in psychometric analysis. In Rasch Measurement: Applications in Quantitative Educational Research (pp. 3–7). Springer Singapore. https://doi.org/10.1007/978-981-15-1800-3_1
Kopp, J. P., & Jones, A. T. (2020). Impact of item parameter drift on Rasch scale stability in small samples over multiple administrations. Applied Measurement in Education, 33(1), 24–33.
Linacre, J. M., George Engelhard, J., Wang, J., Boone, W., Haines, R. T., Royal, K., Marosszeky, N., & Haines, R. T. (2017). Rasch Measurement Transactions. 31(2).
Maric, D., Fore, G. A., Nyarko, S. C., & Varma-Nelson, P. (2023). Measurement in STEM education research: a systematic literature review of trends in the psychometric evidence of scales. International Journal of STEM Education, 10(1), 39. https://doi.org/10.1186/s40594-023-00430-x
Mayer, R. E. (2020). Multimedia Learning (3rd ed.). Cambridge University Press. https://doi.org/DOI: 10.1017/9781316941355
Nunnally, J. C. (1975). Psychometric theory—25 years ago and now. Educational Researcher, 4(10), 7–21.
O’Neill, T. R., Gregg, J. L., & Peabody, M. R. (2020). Effect of sample size on common item equating using the dichotomous Rasch model. Applied Measurement in Education, 33(1), 10–23.
Planinic, M., Boone, W. J., Susac, A., & Ivanjek, L. (2019). Rasch analysis in physics education research: Why measurement matters. Physical Review Physics Education Research, 15(2), 1–14. https://doi.org/10.1103/PhysRevPhysEducRes.15.020111
Saptadi, N. T. S., Septiani, S., Wardoyo, T. H., Hidayati, W., Thoif, M., Talindong, A., Audia, F., Nashiroh, P. K., Hadikusumo, R. A., & Suroya, L. F. (2025). Pendidikan Vokasional: Teori dan Praktik. Sada Kurnia Pustaka.
Siregar, T. (2025). Mengapa Validitas dan Reliabilitas Penting dalam L&D (Pembelajaran & Pengembangan): Apa yang Dapat Anda Lakukan Tentang Hal Ini. JURNAL PEMIKIRAN DAN PENGEMBANGAN PEMBELAJARAN, 7(1), 1–12.
Tajuddin, N. I. I., Abas, U.-H., Aziz, K. A., Nor, R. N. H., Izni, N. A., Sudin, M. N., Anim, N. A. H. M., & Noor, N. M. (2025). Content Validity Assessment Using Aiken’s V: Knowledge Integration Model for Blockchain in Higher Learning Institutions. International Journal of Advanced Computer Science and Applications.
Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53–55. https://doi.org/10.5116/ijme.4dfb.8dfd
Van Zile-Tamsen, C. (2017). Using Rasch analysis to inform rating scale development. Research in Higher Education, 58(8), 922–933.
Vincent, J. I., MacDermid, J. C., King, G. J. W., & Grewal, R. (2015). Rasch analysis of the patient rated elbow evaluation questionnaire. Health and Quality of Life Outcomes, 13(1). https://doi.org/10.1186/s12955-015-0275-8
Wind, S. A., & Lugu, B. (2024). Combining nonparametric and parametric item response theory to explore data quality: Illustrations and a simulation study. Applied Measurement in Education, 37(2), 109–131.
Xue, J., Chen, M., & Su, J. (2025). Evaluating the psychometric quality of classroom english assessments through the Rasch model. Lecture Notes on Language and Literature, 8: 6-13. https://doi.org/http://dx.doi.org/10.23977/langl.2025.080502
Zamanzadeh, V., Ghahramanian, A., Rassouli, M., Abbaszadeh, A., Alavi-Majd, H., & Nikanfar, A.-R. (2015). Design and implementation content validity study: development of an instrument for measuring patient-centered communication. Journal of Caring Sciences, 4(2), 165.
DOI: https://doi.org/10.17509/e.v25i1.94927
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