Pola Beli Konsumen Menggunakan Algoritma Fp-Growth Untuk Rekomendasi Promosi Pada Aneka Jaya Motor - Junta Zeniarja; Kurniawan Ridwan Surohardjo; Agus Winarno (JOINS (Journal of Information System), 2021)
A piece of appropriate information can create and establish a business strategy in increasing sales through technology that can affect the trade-in buying and selling goods with the data information generated can be calculated in detail and accurately. At Aneka Jaya Motor Semarang, this was triggered by the demand for competition. One solution is a product promotion target. For determining which items are feasible for promotion, the application of a promotional decision recommendation system is made using data mining techniques associated with FP-Growth algorithms, its function is to find items that are often purchased simultaneously by consumers. Data used in the form of transaction data with the total amount used 501 data. The results obtained by appearing 1 rule is if consumers buy spark plug parts then buy oil parts with minimum support of 10% and minimum confidence of 35%. The lift ratio obtained is 1 so that valid rules are generated.