JOMLAI: Journal of Machine Learning and Artificial Intelligence
Vol. 1 No. 4 (2022): December

Application of Data Mining Classification to Store Customer Satisfaction Bombay Textiles

Siti Sundari (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)
Agus Perdana Windarto (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)
Yuegilion Pranayama Purba (STIKOM Tunas Bangsa, Pematangsiantar, Indonesia)



Article Info

Publish Date
30 Dec 2022

Abstract

This study aims to obtain a model of rules in classifying the level of customer satisfaction at Bombay Textile Stores. By knowing the level of customer satisfaction, shop owners can improve service if it is not good and further improve service if the level of satisfaction is good. This study measures the level of customer satisfaction at the Bombay Textile Store. The method used in this study is the C4.5 Algorithm, where the data source used is a questionnaire/questionnaire technique given to Bombay Textile Store customers. The variables used include Service, Quality of Goods, Price, Facilities, and Promotion. The results obtained 11 rules for the classification of customer satisfaction levels with 5 rules satisfied status and 6 rules dissatisfied status. The C4.5 algorithm can be used in the case of customer satisfaction levels with an accuracy rate of 96.67%. From the results of the analysis, it is hoped that it can be applied so that it can be used as a decision to improve service to customers.

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Journal Info

Abbrev

jomlai

Publisher

Subject

Computer Science & IT Engineering

Description

Focus and Scope JOMLAI: Journal of Machine Learning and Artificial Intelligence is a scientific journal related to machine learning and artificial intelligence that contains scientific writings on pure research and applied research in the field of machine learning and artificial intelligence as well ...