Klasifikasi Kelancaran Kredit Dengan Metode Random Forest

  • Muhammad Irhamna Putra Universitas Islam Negeri Sunan Ampel
  • Ahmad Yusuf Universitas Islam Negeri Sunan Ampel
  • Nita Yalina Universitas Islam Negeri Sunan Ampel
Keywords: Data Mining, Random Forest, Decision Support System, Credit Risk

Abstract

This research contains the discussion the use of machine learning for doing prediction toward a good loan using random forest algorithm. This prediction will become basic reference for the bank to continue in evaluating credit risk. At this time, the absence of decision support system for doing prediction toward a good loan became a problem to the bank in attempt to reduce the credit risk. Therefore, a decision support system with machine learning modelling using random forest algorithm was built in predicting a good loan. Based on the result of this research, the prediction model being evaluated in several scenarios and having an average result 96,47%

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Published
2020-03-17
How to Cite
PutraM. I., YusufA., & YalinaN. (2020). Klasifikasi Kelancaran Kredit Dengan Metode Random Forest. Systemic: Information System and Informatics Journal, 5(2), 7-12. https://doi.org/10.29080/systemic.v5i2.713
Section
Articles