Implementasi Data Mining dengan Metode Apriori Untuk Analisis Pola Penjualan Barang Fashion - Ardiansyah, Achmad; Midtaqulhuda, M (STIKOM Tunas Bangsa Pematangsiantar, 2022)
Technological developments are quite felt for all lines of life that do not exist in the trading business sector. The proliferation of online stores is one of the impacts of technological developments that change the way consumers think in transactions. Although many online stores appear every year, in fact there are also many online stores that do not last long, because the competition is very tight and the marketing strategy is wrong. Every online store owner is trying to find a strategy so that his store survives. The strategy that can be applied is by providing product recommendations that are in accordance with consumer desires. The ability of shop owners to see consumer wants and needs will have an impact on increasing sales. The ability of the shop owner to organize products and create promotions using certain product combinations. The a priori algorithm is the technique used in this study. In the algorithm, an iteration process is carried out using the minimum support and confidence values to assess each product combination. Then eliminate the combination of items that do not reach the minimum support. Based on this, it is found that the frequency of goods purchased the most simultaneously provides benefits to management in compiling and combining products to optimize marketing. Then take advantage of the confidence value which provides an overview of the relationship between products. Implementation of the a priori algorithm can be used to analyze transaction data for a certain period. So that the results of the information generated by this algorithm can be used in marketing strategies and product promotions that are in accordance with customer desires.