Penggalian Pola Kemampuan Peserta Ujian Berbasis Klaster untuk Penentuan Aturan Sistem Penilaian

Umi Laili Yuhana, Eko M. Yuniarno, Supeno Mardi S. Nugroho, Siti Rochimah, Mauridhi Hery Purnomo

Abstract


Determination of initial ability of examinees is one of the important stages in the adaptive assessment system. The accuracy of the examinee's ability level prediction will influence the appropriateness of choosen item difficulty level for each examinee. This paper discusses the patterns mining of cognitive ability based on cluster using K-Means. The K-means method is utilized to mine the examinees’ ability pattern from examinees’ pretest answers. The patterns are used for developing rules to determine examinee’s ability level in the adaptive assessment system. The addition of this method is proposed to improve the performance of the prediction methods to predict the examinees’ ability level. Extraction of graduation value at each level is done before the pattern excavation process. Patterns found become the basis of making the rules as well as replace the rules from the experts in previous studies. The prediction of participants' ability is done by implementing rule based method classifier. A total of 140 data were used for the experiment. Based on the results of the experiment, it can be concluded that the cluster-based pattern mining using K-means can be utilized to determine the cognitive ability level of examinee. The application of this method to student pretest data shows the performance improvement of all the prediction methods used in this paper, i.e. Naive Bayes, MLP, SMO, Decision Table, JRIP, and J48. This method is suitable for adaptive assessment system where the rules can be adjusted along with the addition of the number of the data as well as the addition of the number of variations in the ability pattern of examinees.

Keywords


sistem penilaian, penentuan tingkat kemampuan peserta, K-means, metode pengklasifikasi berbasis aturan.

Full Text:

PDF

References


R. Yunis and K. Telaumbanua, “Pengembangan E-Learning Berbasiskan LMS untuk Sekolah, Studi Kasus SMA/SMK di Sumatera Utara,” Jurnal Nasional Teknik Elektro dan Teknologi Informasi (JNTETI), vol. 6, no. 1, pp. 32–36, 2017.

S. Schiaffino, P. Garcia, and A. Amandi, “eTeacher: Providing personalized assistance to e-learning students,” Computers and Education, vol. 51, no. 4, pp. 1744–1754, 2008.

D. Syarif and S. Sahid, “Modeling the Flow Experience for Personalized Context Aware E-learning,” in Proceeding of 8th International Conference on Information Technology and Electrical Engineering (ICITEE), 2016.

S. Q. Authority, Guide to Assessment. Scottish Qualifications Authority, 2014.

K. J. Kennedy and J. C. K. Lee, The changing Roles of Schools in Asian Societies: Schools for Knowledge Society. Routledge London and New York, 2008.

Kementerian Pendidikan dan Kebudayaan RI, “Ujian Nasional Berbasis Komputer.” [Online]. Available: https://ubk.kemdikbud.go.id/. [Accessed: 31-Jul-2017].

K. Rajamani and V. Kathiravan, “An adaptive assessment system to compose serial test sheets using item response theory,” Proceeding of the 2013 International. Conference on Pattern Recognition, Informatics and Mobile Engineering, PRIME 2013, pp. 120–124, 2013.

J. Linacre, S. Chae, U. Kang and E. Jeon, “Computer-Adaptive Testing : A Methodology Whose Time Has Come". MESA Memorandum, no. 69, 2000.

N. a. Thompson and D. J. Weiss, “A framework for the development of computerized adaptive tests,” Practical Assessment, Research and Evaluation, vol. 16, no. 1, pp. 1–9, 2011.

S. Agarwal, N. Jain, and S. Dholay, “Adaptive Testing and Performance Analysis using Naive Bayes Classifier,” Procedia - Procedia Computer Science, vol. 45, pp. 70–75, 2015.

I. N. Sukajaya, "Klasifikasi Domain Kognitif Pembelajar Matematika Menggunakan Serious Game Berbasis Taksonomi Bloom", Buku Sidang Terbuka Promosi Doktor Teknik Elektro ITS, 2016.

C. K. Hu lin, C. L., Drasgow, F., & Parsons, “Item response theory application to psychological measurement,” Homewood, Dow Jones-Irwin, 1983.

A. Ismaya, “Algoritma Ekstraksi Informasi Berbasis Aturan,” Jurnal Nasional Teknik Elektro dan Teknologi Informasi (JNTETI), vol. 3, no. 4, pp. 242–247, 2014.

U. L. Yuhana, R. G. Mangowal, S. Rochimah, E. M. Yuniarno, and M. H. Purnomo, “Predicting Math Performance of Children with Special Needs Based on Serious Game,” in The 5th IEEE Conference on Serious Game and Application for Health, 2017.

R. G. Mangowal, U. L. Yuhana, E. M. Yuniarno, and M. H. Purnomo, “MathBharata : A Serious Game for Motivating Disabled Students to Study Mathematics,” in The 5th IEEE Conference on Serious Game and Application for Health, 2017.

Menteri Pendidikan dan Kebudayaan RI, “Permendikbud No 24 Tahun 2016,” 2016.

Menteri Pendidikan dan Kebudayaan RI, “Lampiran Permendikbud No 24 Tahun 2016,” 2016.

Badan Standar Nasional Pendidikan, Standar Kompetensi dan Kompetensi Dasar SD/MI. 2006.




DOI: http://dx.doi.org/10.22146/jnteti.v6i4.357

Refbacks

  • There are currently no refbacks.


Copyright (c) 2017 Jurnal Nasional Teknik Elektro dan Teknologi Informasi (JNTETI)

 

------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Tim Redaksi JNTETI

Jurusan Teknik Elektro dan Teknologi Informasi
Fakultas Teknik Universitas Gadjah Mada
Jl. Grafika No. 2 Kampus UGM Yogyakarta

Telp. +62 0274 552305

Email :
jnteti@ugm.ac.id

 

 

 JNTETI Visitor :

Flag Counter

JNTETI Visitor

 

 Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.