Bankruptcy Prediction Model for Credit Bank Aprovement

In this repository there is a prediction of bankruptcy model for credit bank aprovement made with the Gradient Tree Boosting algorithm. In addition Gradient Tree Boosting algorithm is compared with other classification algorithms. This prediction model was made in research assignment in Financial Computing course at Telkom University on odd semester 2017/2018. For more details see the paper that has been generated on this task at the following link.

Result Paper (in Bahasa)

Reference

[1]J. Heo and J. Y. Yang, "AdaBoost Based Bankruptcy Forecasting of Korean Construction Company," Applied Soft Computing, vol. 24, pp. 494-499, 2014. [2] C.-F. Tsai, "Feature Selection in Bankruptcy Prediction," Knowledge Based System, pp. 120-127, 2009. [3] L. I. Smith, "A tutorial on Principal Components Analysis," 2002. [4] S. Haykin., Neural Network: A Comprehensive Foundation, New Jersey: Prentice Hall, 1999. [5] M. Lichman, "{UCI} Machine Learning Repository," University of California,Irvine, School of Information and Computer Science, 2013. [Online]. Available:http://archive.ics.uci.edu/ml/datasets/statlog+(australian+credit+approval).

Model Prediksi Kredit Macet Dalam Persetujuan Kredit di Bank

Pada repositori ini terdapat pembuatan model prediksi kredit macet yang dibuat dengan algoritma Gradient Tree Boosting. Selain itu algoritma Gradient Tree Boosting dibandingkan dengan algoritma klasifikasi yang lain. Model prediksi ini dibuat dalam tugas riset pada mata kuliah Komputasi Finansial di Universitas Telkom pada semeter ganjil 2017/2018. Untuk lebih detailnya dapat dilihat pada paper yang telah dihasilkan pada tugas ini pada link berikut.

Paper Hasil Penelitian

Referensi

[1]J. Heo and J. Y. Yang, "AdaBoost Based Bankruptcy Forecasting of Korean Construction Company," Applied Soft Computing, vol. 24, pp. 494-499, 2014. [2] C.-F. Tsai, "Feature Selection in Bankruptcy Prediction," Knowledge Based System, pp. 120-127, 2009. [3] L. I. Smith, "A tutorial on Principal Components Analysis," 2002. [4] S. Haykin., Neural Network: A Comprehensive Foundation, New Jersey: Prentice Hall, 1999. [5] M. Lichman, "{UCI} Machine Learning Repository," University of California,Irvine, School of Information and Computer Science, 2013. [Online]. Available:http://archive.ics.uci.edu/ml/datasets/statlog+(australian+credit+approval).