PERBANDINGAN ALGORITMA C4.5 DAN ALGORITMA
NAÃVE BAYES PADA DATA KELULUSAN MAHASISWA
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Institusion
Universitas Katolik Musi Charitas
Author
Kristiono, Agus
Subject
QA75 Electronic computers. Computer science
Datestamp
2022-10-24 03:31:37
Abstract :
Musi Charitas Catholic University (UKMC) is a private university in Palembang. Accreditation is one form or method used to assess the feasibility of a university with predetermined accreditation criteria. One of the criteria for accreditation assessment is the evaluation of the length of study of graduating students. It is important for universities to analyze whether students who have completed the study period have passed on time. Data mining technique is one method that can be used for the classification process. There are five data mining methods: estimation, prediction, classification and association. Classification was carried out using the C4.5 and Naive Bayes algorithms, using the attributes of gender, gender, age, address and GPA. From the comparison results of the C4.5 and Naive Bayes algorithms, it is found that the C4.5 algorithm is better than Naive Bayes. Where the C4.5 algorithm has an accuracy value of 92.43%, while the Naive Bayes algorithm is 91.12% the difference is 1.31%. In addition to the accuracy obtained, precision and recall values are also obtained, where the C4.5 precision is 98.86% and 95.76% for naive Bayes. The recall value for C4.5 is 93.09% and 94.37% for Naive Bayes. Keywords: Data Mining ; Classification ; C4.5 Algorithm ; Naïve Bayes Algorithm ; performance
Musi Charitas Catholic University (UKMC) is a private university in Palembang. Accreditation is one form or method used to assess the feasibility of a university with predetermined accreditation criteria. One of the criteria for accreditation assessment is the evaluation of the length of study of graduating students. It is important for universities to analyze whether students who have completed the study period have passed on time. Data mining technique is one method that can be used for the classification process. There are five data mining methods: estimation, prediction, classification and association. Classification was carried out using the C4.5 and Naive Bayes algorithms, using the attributes of gender, gender, age, address and GPA. From the comparison results of the C4.5 and Naive Bayes algorithms, it is found that the C4.5 algorithm is better than Naive Bayes. Where the C4.5 algorithm has an accuracy value of 92.43%, while the Naive Bayes algorithm is 91.12% the difference is 1.31%. In addition to the accuracy obtained, precision and recall values are also obtained, where the C4.5 precision is 98.86% and 95.76% for naive Bayes. The recall value for C4.5 is 93.09% and 94.37% for Naive Bayes. Keywords: Data Mining ; Classification ; C4.5 Algorithm ; Naïve Bayes Algorithm ; performance
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SI-2022-1814011-abstract.pdf
SI-2022-1814011-tableofcontent.pdf
SI-2022-1814011-cover.pdf
SI-2022-1814011-complete.pdf
SI-2022-1814011-chapter1.pdf
SI-2022-1814011-chapter2.pdf
SI-2022-1814011-chapter3.pdf
SI-2022-1814011-chapter4.pdf
SI-2022-1814011-conclusion.pdf
SI-2022-1814011-reference.pdf
SI-2022-1814011-summary_id.pdf
SI-2022-1814011-attachment.pdf
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