Analisa Perancangan Sistem Informasi Dengan Fitur Rekomendasi Menggunakan Algoritma Apriori - Fathurrozi, Ahmad; Hariyanto; Prio Pamungkas, R Wisnu; Kustanto, Prio; Noeman, Achmad; Handayani, Dwipa (Pandawan Incorporation, Alphabet Incubator Universitas Raharja, 2023)
This Ilham Green Shop has just started an online business by selling types of plants which are a growing business area now, but this Ilham Green Shop only has a few buyers, this is because the Ilham Green Shop has not been seen or heard among the public, so it is necessary a sales information system with a recommendation feature built using the PHP and MySQL programming languages and tested by the blackbox - testing method. Data collection techniques used are observation, interviews, and literature study. For processing sales transaction data using the Apriori Algorithm to get more accuracy in the process of processing data on the plant sales information system to find data on the best-selling plant products and see the buying pattern of a buyer by calculating the minimum support value and minimum confidence value to determine the association rules for a combination of itemset. . The results of the Apriori Algorithm calculation in this sales information system with sales transaction data from 03 December 2021 – 30 May 2022 obtained from Ilham Green Shop obtained the lift test value of 1.55 using the minimum support value = 10%, the minimum confidence value = 40% who form association rules with a confidence value of 93.55%. From these results it can be concluded, by processing plant product data with the Apriori Algorithm, it is able to provide good plant recommendations, so Ilham Green Shop can determine a strategy by multiplying the best-selling plant nurseries to get a lot of profit and recommending them to attract buyers' interest.