Implementasi Sistem Prediksi Penjualan Di Butik Divva-Collection Berbasis Website Menggunakan Metode K-NN
DOI:
https://doi.org/10.36350/jbs.v16i1.335Keywords:
K-NN, Website, MAPE, Sales PredictionAbstract
This study aims to build a website-based sales prediction system at the Divva-Collection Boutique using the K-Nearest Neighbor (K-NN) method. The data used are monthly sales data from several fashion products during the period January 2024 to April 2025. The K-NN method is applied with the Chebyshev distance approach to calculate the closeness between historical data. The K value used is K = 3 because it provides the best level of accuracy based on the test results. The process is carried out by calculating the average of the K nearest neighbors to produce a sales prediction value. Evaluation of the prediction results using the Mean Absolute Percentage Error (MAPE) method shows that all MAPE values are below 10%, with an accuracy level reaching 90%, both from manual calculations using Excel and from the system built. These results indicate that the system has good accuracy and is suitable for use as a tool in sales decision making at the Divva-Collection Boutique.
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