Implementasi Data Mining Pada Klasifikasi Ketidakhadiran Pegawai Menggunakan Metode C4.5

Not all employee absences have reasons that are always labeled as bad. There is also an absence that can be tolerated by an agency or company, where these reasons are acceptable reasons, for example, due to illness, or certain permits that are considered reasonable and of course have a certain period so that it is not too difficult for the party where he works. The research objective is to determine the extent to which the C4.5 algorithm can help the classification calculation to find solutions so that employee works productivity increases. To find a solution so that employee work productivity increases requires certain techniques and methods, namely by classifying data mining using the C4.5 Algorithm. For data processing to get good results, Rapid Miner 5 Tools are used. The C4.5 algorithm is a type of classification rule in Data Mining. The importance of a classification rule can be determined by two parameters, namely Entropy and the highest Gain. After testing, the results obtained from the C4.5 Algorithm have an accuracy of 81.08%.