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All Journal Jurnal Rekayasa Teknologi dan Sains Terapan
Muhammad Alfarisi
President University
Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mathematics Mechanical Engineering Physics

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Predicting Bank Loan Application Approval using Logistic Regression Method Dadang Amir Hamzah; Akbar Jabbarudin; Haura Nizar Nabila; Muhammad Alfarisi; Salwa Fayza Alkatraz; Zievan Ananta Pahlevi
Jurnal Rekayasa Teknologi dan Sains Terapan Vol 4 No 1 (2022): Jurnal Rekayasa Teknologi dan Sains Terapan
Publisher : LPPM, Sekolah Tinggi Teknologi DR. KHEZ Muttaqien

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Abstract

This paper provides an overview of the analysis that affects a bank based on existing data records. By using logistic regression, the dependent variable is a defining feature that determines whether there is an investment or not investment. On the other hand, the independent variables are analyzed by using exploratory data analysis to identify which characteristic has the highest correlation with the dependent variable. Based on selected features, the logistic regression model is created and used to generate the prediction data. The predicted data will provide an excellent approximation for the actual data.
Co-Authors Akbar Jabbarudin Hamzah, Dadang Amir Haura Nizar Nabila Salwa Fayza Alkatraz Zievan Ananta Pahlevi