Penerapan Business Intelligence Terhadap Data Penjualan UMKM (Foodendez) Menggunakan Metode Algoritma Apriori Dalam Menentukan Segmentasi Pasar - Akhmad Rafi Oktavian; Fitrah Rumaisa (STMIK Budi Darma, 2022)
MSMEs in Indonesia are MSMEs with a business scale level of 98.7% are micro-enterprises and this MSME-scale assessment category was assessed or researched 10 years ago, the results are still the same as the previous assessment, due to the average MSMEs in Indonesia not having a way or the right innovation in developing its business, especially in terms of the products produced and other things, an example of MSMEs experiencing this is MSME Foodendez, which causes these MSMEs to not have significant sales progress. Therefore, to improve the quality and progress of the Foodendez MSME business, the current sales data is used to recapitulate and evaluate the Foodendez MSME market segmentation. By using the a priori algorithm, the sales data can be used to find out predictive information on consumer interest based on age, gender, and sales location criteria. The application of business intelligence uses an a priori algorithm so that it can help provide predictive information on consumer interest in a product and can clearly know its market segmentation by collecting data through product sales in the marketplace it can be seen which products are most interested in by consumers, then data on the amount followers, comments, and likes in every post on social media in order to determine engagement (promotional strategies through social media). In this research, testing is carried out based on the location of sales at Foodendez SMEs so as to produce market segmentation data. The conclusion from the temporary test results, the frequency of sales in the marketplace is the highest at 52%, then the lowest frequency of sales is 12% in sales through exhibition bazaars.