Implementation of Data Mining Using C4.5 Algorithm on Customer Satisfaction in Tirta Lihou PDAM - Titin Handayani Sinaga; Anjar Wanto; Indra Gunawan; Sumarno Sumarno; Zulaini Masruro Nasution (Journal of Computer Networks, Architecture and High Performance Computing, 2021)
This application applies the C4.5 Algorithm to decide customer satisfaction, the C4.5 algorithm is one of the algorithms used to classify or segment, or group and it is predictive. This type of research is a classification with the concept of data mining involving 150 customers of PDAM Tirta Lihou in Totap Majawa Kab. Simalungun can be categorized as: "Satisfied and Dissatisfied". The meaning of Data Mining is an interdisciplinary subfield of computer science and statistics with the overall objective of extracting information (with intelligent methods) from data sets and converting information into understandable structures for further use. There are 5 criteria that can affect customer satisfaction, among others: Service Facilities (x1), Price Rates (x2), Smooth Water (x3), Corporate Image (x4), and Location (x5). The results of processing the C4.5 method using the RapidMiner Studio 5.3 software mean that Rapid Miner is a solution for analyzing data mining, text mining, and predictive analysis. Rapid Miner uses various descriptive and predictive techniques in providing insight to users so that they can make the best decisions with the level of accuracy, namely, class recall and class precision values, it is explained that the "Satisfied" category produces a class recall of 97.80% and a class precision of 97.80%. 98.89% and the "Not Satisfied" category resulted in a class recall of 98.31% and a class of precision of 96.67%. And the above accuracy results from the calculation of the C4.5 algorithm is 98.0%. Keywords: C4.5 Algorithm, Data Mining, Customer Satisfaction, PDAM Tirta Lihou