Perbandingan Performa Algoritme Naïve Bayes Dan C4.5 Terhadap Pemahaman Belajar Mahasiswa (Studi Kasus : Selama Pembelajaran Daring Di It Telkom Purwokerto)

Nora, Trivetisia (2023) Perbandingan Performa Algoritme Naïve Bayes Dan C4.5 Terhadap Pemahaman Belajar Mahasiswa (Studi Kasus : Selama Pembelajaran Daring Di It Telkom Purwokerto). Undergraduate Thesis thesis, Institut Teknologi Telkom Purwokerto.

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Abstract

Online learning is a learning system that has been widely implemented since the Covid-19 Pandemic. This learning system is synonymous with the use of internet-based learning media. In practice, teachers often have difficulty knowing how far their students can understand the material being taught. Therefore, it is necessary to do a classification to make it easier for teachers to assess the level of understanding in terms of health, motivation, and teaching methods. Many classification algorithms can be used so that analysis is needed to find the best algorithm. This study focuses on comparative observations of two classification algorithms, namely Naïve Bayes and C4.5. The dataset used is the result of a student questionnaire at the Telkom Purwokerto Institute of Technology in the form of a Likert scale. The steps taken were data preprocessing and then classification using Naïve Bayes and C4.5. The result is that Naïve Bayes is superior to C4.5 in the training process with an accuracy of 98%, an RMSE value of 0.12649, and a computation time of 0.0023963 seconds. Meanwhile, C4.5 with 92% accuracy, RMSE value of 0.27928, and computation time of 0.0027827 seconds. Then, in the Naïve Bayes testing process it is also superior to C4.5 with an accuracy of 99%, an RMSE value of 0.1095, and a computing time of 0.0012893 seconds. Meanwhile, C4.5 with 94% accuracy, RMSE value of 0.2489, and computation time of 0.0015656 seconds. So, it can be concluded that Naïve Bayes is superior to C4.5 in this case. Keywords: C4.5, Classification, Naïve Bayes, Online Learning, Data Mining

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