Tingkat Kepuasan Mahasiswa Terhadap Pelayanan Akademik Diukur Dengan Data Mining C4.5 Menggunakan Metode Decision Tree Dan Naïve Bayes
DOI:
https://doi.org/10.59581/jusiik-widyakarya.v1i4.1777Keywords:
Implementation, Data Mining C4.5, Decision Tree, Naïve Bayes, Rapid MinerAbstract
The goal of this data mining C4.5 implementation is to improve student performance in academic coursework in the computer science department at Teknik Fakultas and Pancasakti University in Tegal. Use a limited number of dimensions to assess the following: nyata, jaminan, keandalan, empatia, dan bukti nyata. It is difficult to determine which quality standard has to be raised because the aforementioned kelima aspek cannot be changed in an objective manner. Utilizing the algorithm C4.5 method, the authors consider reducing the sample size to the point where the keputusan is reduced. After manual perhitungan, pembuktian is also carried out using an application called RapidMiner.The analysis's conclusions show that the most important factor in determining the mahasiswa's tingkat kepuasan is the style of teaching.
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