Application of the C 4.5 Algorithm to Classify Customer Characteristics at PT. Bayer Indonesia - Siswandi, Arif; Anwar, M. Syaibani; Susilo, Arif; Hasibuan, Sultan (Yayasan Cita Cendekiawan Al Khwarizmi, 2024)
PT. Bayer Indonesia is a company engaged in drug production. In running its business, companies need to know customer characteristics in determining what actions to take next. This research aims to apply the C 4.5 algorithm in classifying customer characteristics at PT. Bayer Indonesia. The C 4.5 algorithm is a decision tree algorithm that is often used in data mining for classification purposes. This research was conducted to make it easier to find out customer characteristics. Starting with collecting data, then selecting the attributes that will be used. Then the data is separated using split data, the initial comparison used is 60% train data and 40% test data. Then training data is carried out using the C4.5 algorithm. Next, the classification results were evaluated using the confusion matrix method. The data used was 200 data with 9 attributes, obtained an accuracy of 86.25%, precision of 86.25% and recall of 54.55%. Then change the data split parameters to 70% : 30%, 80% : 20% and 90% : 10%. The best accuracy is 100%. The research results show that the C 4.5 algorithm has good performance in classifying the characteristics of PT customers. Bayer Indonesia. The resulting model can be used by companies for more effective marketing strategies and personalized customer service.