Currently, UP3 Manokwari electrical distribution network (feeder distribution network) still has problems in knowing the location of the disruption, and classifying the points and types of disruption. It also has a manual recording of disruption reports, indirect recaps of detailed disruption reports, and ineffective delivery of disruption-related information to field officers (yantek) and leaders. The purpose of this study is to obtain a pattern or node using the C4.5 algorithm in classifying points and types of feeder distribution network disruption and assist officers in recording details of disruption in real-time. Pattern evaluation using Rapidminer tools and using Confusion Matrix to test the accuracy of the classification method. The results showed that the classification of disruption points was determined by the disruption load factor and relay with 3 (three) patterns/nodes. In comparison, the classification of disruption types was determined by the damage factor and the cause of the disruption with 16 patterns/nodes. The accuracy level of the C4.5 algorithm model was 87.80. % for classification of disruption types and 96.15% for classification of disruption points.