Performance Comparison of Data Mining Algorithms Which Occupy the Top: C4.5 and SVM

Indri Tri Julianto (STMIK LIKMI)
Ricky Rohmanto (STMIK LIKMI)
Ujang Sarifudin (STMIK LIKMI)
Septian Rheno Widianto (STMIK LIKMI)

Jurnal Mantik
Vol. 4 No. 4 (2021): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)

Data is a collection of various kinds of facts that are stored but do not have meaning. Mining is a mining process. So data mining can be interpreted as the process of mining large and complex amounts of data for new knowledge or information that can be useful for data owners. There is a sequence of systematic ways to solve problems in Data Mining, known as Data Mining algorithms. The IEEE International Conference on data mining which was conducted in 2006 produced the 10 most frequently used data mining algorithms by the research community around the world. Two of the ten most commonly used algorithms are the C4.5 algorithm and the Support Vector Modeling (SVM) algorithm. The methodology used in this research is The Knowledge Discovery in Database (KDD) stage. This study aims to compare the C4.5 with the SVM in terms of performance where what will be seen is the value of Area Under Curve (AUC), Receiver Operating Characteristic (ROC), Accuracy, Error, Precison, and Recall.