Simulation Model for Predicting Banking Customers Satisfaction Using Chi-Square Test & Naïve Bayes Classifier

Simulation Model for Predicting Banking Customers Satisfaction Using Chi-Square Test & Naïve Bayes Classifier.

Mahesh Mahajan                                                                         Reeta Singh

Assistant Professor,                                                                     Assistant Professor,

SVKM’s Institute of Technology, Dhule(M.S.)                        ASM’s IMCOST, Thane(M.S.)

mahesh.mahajan@svkm.ac.in                                                   reeta.singh27july@gmail.com

Abstract:

Today, it is necessary for all Public, Private and Government bank to find their banking customers satisfaction ratio depending on feedback provided by the customers. These research paper is useful for finding Personal Characteristics and Banking Behavior of Customers. The study uses primary data which was collected from 550 responders.  The responders are taken from different profession and different age group. The bank can offer different kind of services like ATM, Net banking, Mobile banking and so on. The objective of the paper is to find the result of customer satisfaction. The result is found by Non-probabilistic technique chi- Square test and probabilistic technique Naïve Bayes Classifier. The chi-square test (symbolized as χ2) is basically done by analyzing the data of the agreed upon method for the difference between variables. It is usually a comparison of two statistical data. Naive Bayes algorithm is based on Bayes theorem and is used to solve classification problems. The result of study indicates both positive and negative influence on banking customer behavior.

Keywords

Simulation, chi-square test, Naïve Bayes Classifier, demographic segmentation, customer behaviors.