An Analysis of Students’ Learning Interest in Programming Language Based on Data Mining with Fuzzy C-Means Method

Authors

  • Sitti Aisa Department Technical Information, STMIK Dipanegara
  • Asmah Akhriana Department Technical Information, STMIK Dipanegara
  • Ahyuna Ahyuna Department Technical Information, STMIK Dipanegara
  • Andi Irmayana Department Technical Information, STMIK Dipanegara
  • Irmawati Irmawati Department Technical Information, STMIK Dipanegara
  • Nurul Aini Department Software Engineering, STMIK Dipanegara

DOI:

https://doi.org/10.3991/ijoe.v17i09.24595

Keywords:

— Data Mining, Clustering, Fuzzy C-Means, Programming

Abstract


Students' learning interest and motivation in programming language to date are determined by their scores and abilities to create applications. However, this is not sufficient to identify students' learning interest in programming language because some students got low scores. This study aims to identify students' learning interest in Dipanegara school of informatics management and computer (STMIK), Makassar, in Java programming language. The samples were 65 technical information students and 63 information system students. The data collection technique of this study was questionnaire and processed with data mining technique. Additionally, Fuzzy C-Means clustering method was applied on Java Netbeans programming language to classify the level of students' interest in studying Java programming language.   The result of the study was a web-based application that could determine students’ learning interests. It was obtained through questionnaires and resulted as follows: 47 students had high learning interest, 45 students had moderate interest, and 36 students had fair interest out of 128 samples.

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Published

2021-09-27

How to Cite

Aisa, S., Akhriana, A., Ahyuna, A., Irmayana, A., Irmawati, I., & Aini, N. (2021). An Analysis of Students’ Learning Interest in Programming Language Based on Data Mining with Fuzzy C-Means Method. International Journal of Online and Biomedical Engineering (iJOE), 17(09), pp. 4–20. https://doi.org/10.3991/ijoe.v17i09.24595

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Papers