Analisis Bank Marketing Menggunakan Klasifikasi Machine Learning Untuk Memperoleh Segmentasi Klien Membuka Akun Rekening Deposito Berjangka

Siti, Amalia Permata Saleh (2022) Analisis Bank Marketing Menggunakan Klasifikasi Machine Learning Untuk Memperoleh Segmentasi Klien Membuka Akun Rekening Deposito Berjangka. Project Report. Institut Telkom Telkom Purwokerto. (Unpublished)

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Abstract

This research aims to analyze the campaign activities carried out by a bank. By analyzing the campaign activity data, several important features are obtained that must be considered by the bank to improve the quality of the next campaign. These features are used to help the bank see what segments are important from the bank's clients/customers that need attention so that it becomes the bank's focus/target for clients to be offered to open a time deposit bank account. The method used is Machine Learning with a Gradient Boost Classifier model, where this method works to classify so as to obtain a classification. The results obtained from this analysis are that the Gradient Boost Classifier is a model with an accuracy value of 90.33% with results for classifying data. The important features of the acquisition are: duration , days, contact, month, poutcome and housing respectively. The client segments obtained to be the focus/target for opening a time deposit account are clients in the age category of 20s or younger and 60s or older, with student and retired employment status, and do not have personal loans.

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