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All Journal Majalah Ilmiah METHODA
Hutagalung, Jessica Uly Sari
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Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Medicine & Pharmacology Public Health

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Identifikasi Potensi Penipuan pada Transaksi Bank Menggunakan K-Means Clustering Hutagalung, Jessica Uly Sari; Sihombing, Kristin Trivena; Hutabarat, Michael Owen; Irviantina, Syanti
Majalah Ilmiah METHODA Vol. 14 No. 3 (2024): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol14No3.pp392-395

Abstract

Increasing cases of fraud in bank transactions are a serious concern for financial institutions, resulting in significant economic losses and undermining customer trust. This calls for identifying suspicious transaction patterns through machine-learning approaches to mitigate the risk of fraud. The methods used include problem identification, transaction data collection, and preprocessing to clean and prepare the data and after that, applying the K-Means Clustering algorithm to group transactions based on similar characteristics. The evaluation result obtained in this study using the Silhouette Score is 0.42, indicating a fairly good separation between normal and suspicious transactions. This research is expected to contribute to the development of a more accurate and efficient machine learning-based fraud detection system in banking institutions.
Co-Authors Hutabarat, Michael Owen Sihombing, Kristin Trivena Syanti Irviantina