Penerapan Decision Tree Algoritma C4.5 Dalam Penentuan Izin Pembongkaran Muatan Kapal - Kusuma, Jaka; Jinan, Abwabul; Situmorang, Zakarias (LPPM UNIKA Santo Thomas Medan, 2022)
Along with the increasing number of bulk cargoes that are dismantled every year at belawan port and for the creation of services in accordance with expectations, it is necessary to develop services in support of indonesia's logistics improvement readiness, especially in terms of demolition. Utilization of machine learning using the C4.5 algorithm can make it easier to conduct selection and classification of the feasibility of ships that get permission for demolition activities. The use of the C4.5 algorithm will produce a decision tree that can equalize the results of data mining, so that the information obtained from the data will be easier to identify in testing methods using the Orange Data Mining tool. The results obtained by the C4.5 algorithm in the form of a decision tree with an accuracy value of 84%, 90% precision and 84% recall.