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All Journal International Journal of Computer and Information System (IJCIS)
Ridlo Muttaqien
Univeritas Alma Ata
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Implementation of Data Mining Using C4.5 Algorithm for Predicting Customer Loyalty of PT. Pegadaian (Persero) Pati Area Office Ridlo Muttaqien; Musthofa Galih Pradana; Andri Pramuntadi
International Journal of Computer and Information System (IJCIS) Vol 2, No 3 (2021): IJCIS : Vol 2 - Issue 3 - 2021
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v2i3.36

Abstract

PT Pegadaian (Persero) is engaged in the business of providing credit services with pawn, non-pawning and gold investment products. One of the right marketing strategies to survive today's high competition is to maintain customer loyalty, researchers use several data variables available in the MIS (Management Information System) in the form of customer transaction frequency, how many products are taken by customers, customer satisfaction and direct interviews. to predict customer loyalty of PT Pegadaian (Persero) by implementing the c4.5 algorithm. The c4.5 algorithm is the algorithm used to create a decision tree. Decision trees are a very powerful and well-known method of classification and prediction. The decision tree method converts very large facts into a decision tree that represents the rule. Rules can be easily understood in natural language. This study aims to determine the accuracy of the C4.5 algorithm to predict customer loyalty of PT Pegadaian (Persero) and the most influential factors in loyalty. The results of the experimental application of the c4.5 algorithm show that the level of accuracy generated in predicting customer loyalty is quite high, namely 89.94% in data testing 1 and 94% in data testing 2. The application of the c4.5 algorithm in predicting customer loyalty of PT Pegadaian (Persero) can be well applied.
Co-Authors Andri Pramuntadi Musthofa Galih Pradana