MultiClass Decision Forest Machine Learning Artificial Intelligence

Bambang Siswoyo

doi:10.30871/jaic.v4i1.1155

Bambang Siswoyo STKOM Al-Ma’soem Jatinangor JABAR

DOI: https://doi.org/10.30871/jaic.v4i1.1155

Keywords: Artificial intelligence, Machine Learning, Modeling, Multi Class Decesion Forest

Abstract

Artificial intelligence is the best solution in dealing with various fields. The Multi Class Decesion Forest Machine Learning algorithm which is part of artificial intelligence is an interesting field to be applied in the banking field. This research was developed to build a model that can predict and evaluate bankruptcy in the banking industry. The predictor variable is the financial ratio obtained from the publication of the site http://www.idx.co.id. Modeling machine learning with six variables, where five variables as input and one variable as a target. Overall, the Multi Class Decistion Forest Machine Learning is able to train data input-output relationships and modeling behavior well, 92% accuracy value, 92% precision value and 90% under area curve value.

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