Prediksi Pola Penjualan Produk Herbal Menggunakan Algoritma FP-Growth

Abstract

The sales pattern in principle is a need to build and develop a business, so that the progress of a business needs a strategic pattern to be able to increase sales. One pattern that can be applied is the sale of herbal products, because the herbal product business if it has the right pattern can certainly increase sales results and convenience for sellers and buyers compared to manual settings. The arrangement of the composition of herbal products can make it easier for customers to choose related products. Sustainable product predictions can be easily recognized by sellers. The prediction of sales patterns in this study uses transaction data as many as 33 sales transactions in less than the last three months sourced from sales of herbal products from HNI Business Center 2 Batam. Based on sales analysis using the FP-Growth algorithm, it has been able to predict the sales pattern of herbal products in the future. Furthermore, the transaction data is processed using Rapidminer Studio version 9.0 software with a total of 68 transaction data, so from the results of testing this method, the percentage of success is 80%. The comparison uses 10 samples of sales data. Opportunities to choose interrelated products are very helpful for customers when shopping and predicting future customer needs. Prediction of sales pattern has been able to help in overcoming the instability of herbal product inventory at HNI Business Center 2 Batam.

Penerapan Data Mining Dalam Menentukan Pola Penjualan Sepatu Menggunakan Algoritma FP-Growth

“…Penelitian yang menggunakan algoritma FP-Growth sudah banyak sekali yang melakukannya, seperti penelitian yang dilakukan oleh Supinah, dkk (2022) mengenai prediksi pola penjualan produk herbal menggunakan algoritma FP-Growth, dimana pola peletakan produk herbal dari HNI Bussiness Centre 2 Batam yang sudah ada akan diperbaharui dengan menggunakan algoritma ini. Hasil dari penelitian ini, dapat membantu perusahaan dalam memprediksi kebutuhan customer kedepannya dengan membuat pola peletakan produk penjualan yang saling berkaitan [10].…”