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Diaz Aditya, Erindra Reynaldi
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Computer Science & IT

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Optimizing Bank Marketing Strategies Through Analysis Using Lightgbm Diaz Aditya, Erindra Reynaldi; Yudha Satria, Dhian Kartika
CoreID Journal Vol. 1 No. 2 (2023): July 2023
Publisher : CV. Generasi Intelektual Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60005/coreid.v1i2.11

Abstract

Marketing campaigns in a bank are one of the ways for the bank to achieve its organizational goals. Optimal marketing is a crucial factor for a bank's success in attracting and retaining customers. Therefore, if a bank's marketing campaigns are carried out suboptimally, it will be challenging to achieve the goals of those campaigns. In this case study, it can be observed that the number of customers who subscribe to fixed-term deposits is lower, with a proportion of 5289 customers making deposits and 5873 customers not making deposits. This research aims to optimize bank marketing strategies by applying analysis using the LightGBM algorithm, which is a highly effective and efficient Gradient Boosting Decision Tree algorithm. This approach facilitates the design of more optimal marketing strategies. The accuracy score of the predictive model generated is 0.8584, with an F1 score of 0.8564, including 974 true negatives and 943 true positives.
Co-Authors Yudha Satria, Dhian Kartika