Penerapan Metode C4.5 Berbasis Particle Swarm Optimization Untuk Memprediksi Penjualan Obat Pada Apotek Bunda Azka

Abstract

The application of the C4.5 Algorithm based on Particle Swarm Optimization to classify the level of sales of drugs that are often sold at the Bunda Azka Pharmacy, is a strategic thing to reduce the problems experienced by the pharmacy. Classify the level of sales of drugs sold using the C4.5 method. based on particle swarm optimization, to find out whether the C4.5 method based on particle swarm optimization (PSO) can optimize drug sales in the future. This research method uses a descriptive method, namely by conducting case study research by studying activities in the field, observing and interviewing stakeholders. in the initial step of this research is the determination of the attributes that will be processed into data mining with the help of rapidminer tools, this study the author uses the KDD model as a standardization in the data mining process. at the pharmacy. The data will later be processed using the c4.5 algorithm based on Particle Swarm Optimization to find the accuracy results of the prediction of the data. The data sample used is the number of 65 drug transaction records at the Bunda Azka Pharmacy. In the test results, the accuracy of Particle Swarm Optimization was 78.10%, for class recall drug sales was 72.50% and after using Particle Swarm Optimization increased to 78.33%, while precision had an accuracy of 77.92% and after using Particle Swarm Optimization increased to 80.33%. From the results of testing with Particle Swarm Optimization, there is an increase in accuracy of 7.15% from the research application of the C4.5 Method Based on Particle Swarm Optimization to Predict Drug Sales at Bunda Azka Pharmacy.