Analisa Terhadap Perbandingan Algoritma Decision Tree Dengan Algoritma Random Tree Untuk Pre-Processing Data

Saifullah Saifullah, Muhammad Zarlis, Zakaria Zakaria, Rahmat Widia Sembiring


Preprocessing data is needed some methods to get better results. This research is intended to process employee dataset as preprocessing input. Furthermore, model decision algorithm is used, random tree and random forest. Decision trees are used to create a model of the rule selected in the decision process. With the results of the preprocessing approach and the model rules obtained, can be a reference for decision makers to decide which variables should be considered to support employee performance improvement

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