Pemanfaatan Klasifikasi Soal Biologi Cognitive Domain Bloom’s Taxonomy Menggunakan KNN Chi-Square Sebagai Penyusunan Naskah Soal

  • Indah Listiowarni Universitas Madura
  • Nindian Puspa Dewi Universitas Madura
Keywords: bloom’s taxonomy, KNN, chi-square, text mining, classification

Abstract

The question manuscript is a document that contains a collection of exam questions that are commonly used by an educator to test the absorption of their students on the material that has been presented in class. Question manuscripts made by educators are made based on a pre-made question grid, and contain a certain percentage of each cognitive domain category in the bloom taxonomy. The level in the bloom taxonomic cognitive domain describes the level of difficulty of each item made, so that an educator must first make a formula in a planning script called a question grid. The items that have been classified based on the cognitive domain taxonomic level of bloom using the KNN classifier method and the Chi-square feature selection are proven to be the right combination, the classification results of these items will be used for the preparation of a text for exam questions with an adjusted percentage formula. With the question grid that has been made beforehand, it is hoped that this research can be used to facilitate educators in drafting appropriate exam questions for their students

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References

Rozi, “upaya kepala sekolah dalam meningkatkan kompetensi guru akidah akhlak dalam menyusunan naskah soal (Studi Kasus di MIN 02 Bengkulu Selatan),” An-Nizom, vol. 5, no. 1, pp. 17–26, 2017.

D. C. Rohim, “Strategi Penyusunan Soal Berbasis HOTs pada Pembelajaran Matematika SD,” J. Ris. dan Konseptual, vol. 4, no. 4, pp. 436–446, 2019, [Online]. Available: http://www.jurnal.unublitar.ac.id/ index.php/briliant.

F. A. Adesoji, “Bloom Taxonomy Of Educational Objectives And The Modification Of Cognitive Levels,” Adv. Soc. Sci. Res. J., vol. 5, no. 5, pp. 292–297, 2018, doi: 10.14738/assrj.55.4233.

A. R. Setiawan, “Penyusunan Program Pembelajaran Biologi Berorientasi Literasi Saintifik,” Semin. Nas. Sains dan Entrep., vol. VI, no. 23, pp. 1–8, 2019, doi: 10.31226/osf.io/etg5n.

N. R. Mujib, A. J. . Toenlioe, and H. Praherdhiono, “analisis butir soal ujian nasional ipa sd/mi tahun 2015 sampai dengan 2017 berdasarkan taksonomi bloom,” Jktp, vol. 1, no. 2, pp. 149–158, 2018.

I. Listiowarni and E. R. Setyaningsih, “Feature Selection Chi-Square dan K-NN pada Pengkategorian Soal Ujian Berdasarkan Cognitive Domain Taksonomi Bloom,” J. Komput. Terap., vol. 4, no. 1, pp. 21–30, 2018.

A. Wijaya, A. Eresti, Despa, and A. Walid, “analisis butir soal persiapan ujian nasional ipa smp/mts tahun 2018 sampai dengan 2019 berdasarkan taksonomi bloom,” LENSA (Lentera Sains) J. Pendidik. IPA, vol. 9, no. 2, pp. 57–63, 2019.

D. A. Abduljabbar and N. Omar, “Exam questions classification based on Bloom’s taxonomy cognitive level using classifiers combination,” J. Theor. Appl. Inf. Technol., vol. 78, no. 3, pp. 447–455, 2015.

S. F. Kusuma, D. Siahaan, and U. L. Yuhana, “Automatic Indonesia’s questions classification based on bloom’s taxonomy using Natural Language Processing a preliminary study,” 2015 Int. Conf. Inf. Technol. Syst. Innov. ICITSI 2015 - Proc., pp. 0–5, 2016, doi: 10.1109/ICITSI.2015.7437696.

T. Setiyorini and R. T. Asmono, “Penerapan Gini Index Dan K-Nearest Neighbor Untuk Klasifikasi Tingkat Kognitif Soal Pada Taksonomi Bloom,” J. Pilar Nusa Mandiri, vol. 13, no. 2, pp. 209–216, 2017.

C. Tristianto, “penggunaan metode waterfall untuk pengembangan sistem monitoring dan evaluasi pembangunan pedesaan,” J. Teknol. Inf. ESIT, vol. XII, no. 01, pp. 41–56, 2018, doi: 10.5749/j.cttttv6b.5.

A. Suryadi, “Perancangan Aplikasi Game Edukasi Menggunakan Model Waterfall,” J. Petik, vol. 3, no. 1, p. 8, 2018, doi: 10.31980/jpetik.v3i1.352.

R. Utari, “TAKSONOMI BLOOM Apa dan Bagaimana Menggunakannya?,” Freshw. Biol., vol. 6, no. 4, pp. 301–315, 2017, doi: 10.1111/j.1365-2427.1976.tb01616.x.

K. Jayakodi, M. Bandara, and I. Perera, “An Automatic Classifier for Exam Questions in Engineeering : A Process for Bloom’s Taxonomy,” IEEE Int. Conf. Teaching, Assessment, Learn. Eng., no. December, pp. 195–202, 2015.

B. Said and F. Prasetyo E.P., “Layanan e-Surat Berbasis Mobile Application di Desa Waru Barat Pamekasan,” InfoTekJar (Jurnal Nas. Inform. dan Teknol. Jaringan), vol. 4, no. 1, pp. 111–115, 2019, doi: 10.30743/infotekjar.v4i1.1637.

Z. Sharfina and H. B. Santoso, “An Indonesian adaptation of the System Usability Scale (SUS),” 2016 Int. Conf. Adv. Comput. Sci. Inf. Syst. ICACSIS 2016, pp. 145–148, 2017, doi: 10.1109/ICACSIS.2016.7872776.

U. Ependi, F. Panjaitan, and H. Hutrianto, “System Usability Scale Antarmuka Palembang Guide Sebagai Media Pendukung Asian Games XVIII,” J. Inf. Syst. Eng. Bus. Intell., vol. 3, no. 2, p. 80, 2017, doi: 10.20473/jisebi.3.2.80-86.

D. W. Ramadhan, “Pengujian usability website time excelindo menggunakan system usability scale (sus) (studi kasus: website time excelindo),” JIPI (Jurnal Ilm. Penelit. dan Pembelajaran Inform., vol. 4, no. 2, p. 139, 2019, doi: 10.29100/jipi.v4i2.977.

Y. D. Setiyaningrum, A. F. Herdajanti, C. Supriyanto, and Muljono, “Classification of twitter contents using chi-square and K-nearest neighbour algorithm,” Proc. - 2019 Int. Semin. Appl. Technol. Inf. Commun. Ind. 4.0 Retrosp. Prospect. Challenges, iSemantic 2019, pp. 78–81, 2019, doi: 10.1109/ISEMANTIC.2019.8884290.

C. F. Suharno, M. A. Fauzi, and R. S. Perdana, “Klasifikasi Teks Bahasa Indonesia Pada Dokumen Pengaduan Sambat Online Menggunakan Metode K-Nearest Neighbors Dan Chi-square,” Syst. Inf. Syst. Informatics J., vol. 3, no. 1, pp. 25–32, 2017, doi: 10.29080/systemic.v3i1.191.

O. S. Bachri, Kusnadi, M. Hatta, and O. D. Nurhayati, “Feature selection based on CHI square in artificial neural network to predict the accuracy of student study period,” Int. J. Civ. Eng. Technol., vol. 8, no. 8, pp. 731–739, 2017.

Y. Yang and J. Pedersen, “A Comparative Study on Feature Selection in Text Categorization,” 1997.

M. Danil, S. Efendi, and R. Widia Sembiring, “The Analysis of Attribution Reduction of K-Nearest Neighbor (KNN) Algorithm by Using Chi-Square,” J. Phys. Conf. Ser., vol. 1424, no. 1, 2019, doi: 10.1088/1742-6596/1424/1/012004.

F. F. Laksana and S. Suyoto, “Pengukuran Kualitas Ux Website Menggunakan Sus,” Comput. Eng. Sci. Syst. J., vol. 4, no. 2, p. 138, 2019, doi: 10.24114/cess.v4i2.12928.

Published
2020-11-01
How to Cite
Listiowarni, I., & Puspa Dewi, N. (2020). Pemanfaatan Klasifikasi Soal Biologi Cognitive Domain Bloom’s Taxonomy Menggunakan KNN Chi-Square Sebagai Penyusunan Naskah Soal. Digital Zone: Jurnal Teknologi Informasi Dan Komunikasi, 11(2), 185-195. https://doi.org/10.31849/digitalzone.v11i2.4798
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