2022
DOI: 10.32520/stmsi.v11i1.1638
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Implementation of Fuzzy C-Means to Determine Student Satisfaction Levels in Online Learning

Abstract: Pembelajaran secara online merupakan solusi yang terbaik di masa pandemi covid-19, sehingga menyebabkan perbedaan pada proses pembelajaran yang biasanya dilakukan dosen secara tatap muka dengan mahasiswa. Perubahan proses pembelajaran ini diharapkan dapat dilaksanakan secara efektif dan efisien. Tujuan dari penelitian ini untuk mengetahui bagaimana tingkat kepuasan mahasiswa dalam pembelajaran online dan menghasilkan sistem yang dapat meng-cluster tingkat kepuasan mahasiswa dengan menggunakan metode Fuzzy C-Me… Show more

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“…In addition to this research, there are several studies that have been conducted by researchers related to the application of data mining methods and the creation of application systems, including research on the classification of student scientific papers using the naive bayes classifier method. [21], The implementation of fuzzy c-means to determine the level of student satisfaction in online learning [22], application of data mining to determine recipients of non-cash food assistance using the k-nearest neighbor method [23], decision support system for determining PKH acceptance using the naïve bayes method [24], application of the profile matching analysis method to the decision support system for study program recommendations [25] and implementation of data mining to analyze student competition categories using the apriori algorithm [26]…”
Section: T H Ementioning
confidence: 99%
“…In addition to this research, there are several studies that have been conducted by researchers related to the application of data mining methods and the creation of application systems, including research on the classification of student scientific papers using the naive bayes classifier method. [21], The implementation of fuzzy c-means to determine the level of student satisfaction in online learning [22], application of data mining to determine recipients of non-cash food assistance using the k-nearest neighbor method [23], decision support system for determining PKH acceptance using the naïve bayes method [24], application of the profile matching analysis method to the decision support system for study program recommendations [25] and implementation of data mining to analyze student competition categories using the apriori algorithm [26]…”
Section: T H Ementioning
confidence: 99%