Telemarketing Bank Success Prediction using Multilayer Perceptron (MLP) Algorithm with Resampling

Telemarketing Bank Success Prediction using Multilayer Perceptron (MLP) Algorithm with Resampling

• By Masturoh, Siti;
• Jurnal Nasional Terakreditasi
• 322
• 19-24

Telemarketing is a promotion that is
considered effective for promoting a product to
consumers by telephone, other than that
telemarketing is easier to accept because of its
direct nature of offering products to consumers.
Telemarketing is also considered to help increase a
company's revenue. The problem of predicting the
success of a bank's telemarketing data must be done
using machine learning techniques. Machine
learning used in the available historical data is a
bank dataset of 45211 instances at 17 features using
the multilayer perceptron algorithm (MLP) with
resampling. The use of resampling aims to balance
the unbalanced data resulting in an accuracy value
of 90.18% and a ROC of 0.89%. Meanwhile, if the
data resampling is not used in the multilayer
perceptron (MLP) algorithm, the accuracy value is
88.6 and ROC is 0.88%. The use of resampling data
becomes more effective and results in higher
accuracy values

• Katakunci Telemarketing; Multilayer Perceptron (MLP); Resampling
• URL http://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/2168
• Penerbit ,

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