PREDICTING CUSTOMERS LOYALTY USING RANDOM FOREST

The research in this paper is about a Machine Learning algorithm namely Random Forest and its application in solving problems related to classification. The classification problem discussed in this paper is about predicting banks’ customers loyalty using parameters contained in the customers dataset...

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Main Author: Belva, Ahmad
Format: Final Project
Language:Indonesia
Subjects:
Online Access:https://digilib.itb.ac.id/gdl/view/52956
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:52956
spelling id-itb.:529562021-02-24T09:38:44ZPREDICTING CUSTOMERS LOYALTY USING RANDOM FOREST Belva, Ahmad Ilmu alam dan matematika Indonesia Final Project machine learning, decision tree, random forest, customers’ loyalty, classification, algorithm INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/52956 The research in this paper is about a Machine Learning algorithm namely Random Forest and its application in solving problems related to classification. The classification problem discussed in this paper is about predicting banks’ customers loyalty using parameters contained in the customers dataset. One of the prominent problems faced by banks in banking industry is about optimizing marketing cost during funding process. On banking sector, marketing cost is used to provide incentive and benefits for customers that already utilize said bank’s service and to attract new potential customers. By predicting customers’ loyalty, banks can optimize their marketing cost by adjusting incentive to existing customers proportional to their predicted loyalty. Random Forest algorithm will be used to build a model that could predict customers’ loyalty based on parameters provided in customers dataset. From experiments done in this research, the model obtained could predict customers’ loyalty sufficiently well represented by the obtained 96% Accuracy, 94% Precision, and 98% Recall. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
topic Ilmu alam dan matematika
spellingShingle Ilmu alam dan matematika
Belva, Ahmad
PREDICTING CUSTOMERS LOYALTY USING RANDOM FOREST
description The research in this paper is about a Machine Learning algorithm namely Random Forest and its application in solving problems related to classification. The classification problem discussed in this paper is about predicting banks’ customers loyalty using parameters contained in the customers dataset. One of the prominent problems faced by banks in banking industry is about optimizing marketing cost during funding process. On banking sector, marketing cost is used to provide incentive and benefits for customers that already utilize said bank’s service and to attract new potential customers. By predicting customers’ loyalty, banks can optimize their marketing cost by adjusting incentive to existing customers proportional to their predicted loyalty. Random Forest algorithm will be used to build a model that could predict customers’ loyalty based on parameters provided in customers dataset. From experiments done in this research, the model obtained could predict customers’ loyalty sufficiently well represented by the obtained 96% Accuracy, 94% Precision, and 98% Recall.
format Final Project
author Belva, Ahmad
author_facet Belva, Ahmad
author_sort Belva, Ahmad
title PREDICTING CUSTOMERS LOYALTY USING RANDOM FOREST
title_short PREDICTING CUSTOMERS LOYALTY USING RANDOM FOREST
title_full PREDICTING CUSTOMERS LOYALTY USING RANDOM FOREST
title_fullStr PREDICTING CUSTOMERS LOYALTY USING RANDOM FOREST
title_full_unstemmed PREDICTING CUSTOMERS LOYALTY USING RANDOM FOREST
title_sort predicting customers loyalty using random forest
url https://digilib.itb.ac.id/gdl/view/52956
_version_ 1822929192160854016