Implementasi Algoritma C4.5 Untuk Analisa Data Illegal Logging

Abstract

Data mining is an information discovery by extracting information partterns that contain trend searches in a large amount of data that helps the process of storing data in making a decision in the future. In determining then pattern classification techniques do to collect records (training data). Forests are an important role that is very important for nation and state development. Because forests can provide maximum benefits. However, that current state of illegal logging has experienced a drastic reduction in area, therefore utilizing illegal logging data can produce information about illegal logging that is a priority and which is not a priority and which is not a priority to be cut down or handled first so that the forest function is correct in its use. Algorithm C4.5 or commonly known as the decision tree method can provide rule data information to describe the processes associated with processing illegal logging data. The characteristic of the classified data can be obtained clearly, both in the form of decision tree structures and in the form of rules. So that in the testing phase with WEKA software can assist in processing valid illegal logging.