Implementation of Gradient Boosted Tree, Support Vector Mach…

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2023
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  • DOI 10.60083/jidt.v5i3.386
  • OpenAlex ID W4387314690
  • Type Article
  • Language EN
  • Published 22 Aug 2023
  • Volume 5 (3)
  • Pages 26–30
  • Source Jurnal Informasi dan Teknologi
  • Publisher Universitas Putra Indonesia "YPTK"
  • FWCI 0.43
  • Countries 1
  • Institutions 5
  • Added 10 Oct 2025
  • Updated 22 Oct 2026
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Implementation of Gradient Boosted Tree, Support Vector Machinery and Random Forest Algorithm to Detecting Financial Fraud in Credit Card Transactions

Article 2023 EN Diamond

According to Google Trends data, machine learning-based credit card identification has grown over the last five years, at the very least, across all nations. In order to detect credit card fraud in this study, the authors will use machine learning methods such random forests, support vector machines, and gradient-boosted trees. The authors used the Synthetic Minority Oversampling Technique (SMOTE)…

5

Citations

13

References

5

Authors

0.43

FWCI

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5 authors
#AuthorInstitutionsORCID
1 Ferdinand Salomo Leuwol Universitas Pattimura (ID)
2 Asri Ady Bakri Universitas Muslim Indonesia (ID)
3 Muhsin N. Bailusy Khairun University (ID)
4 Hari Setia Putra Universitas Negeri Padang (ID)
5 Ni Ketut Sukanti Universitas Ngurah Rai (ID) —

Data: OpenAlex