Rancang Bangun Aplikasi Prediksi Kebiasaan Pelanggan dengan Metode Association Rule Mining (ARM) (Studi Kasus Perusahaan Digital Printing) - Lestari Handayani; Iwan Iskandar; Gatot Suroto (Seminar Nasional Teknologi Informasi Komunikasi dan Industri, 2016)
Availability of detailed data customer transactions is the largest operation undertaken by a digital printing company. Digital printing company should have the customer database. The problem of company to keep consumer loyalty is how to make prediction of customer habits that appropriate with type and target customer market. This system is a system prediction of customer habits that built using the Association Rule Mining Method. Association mining is method mining technique to find the rules of assosiative between combination itemset, the calculation is done by determining the value of minimum support and minimum confidence. The result of best rule calculation used as a combination product recommendations that offered to customers when the transaction took place and can use to reference in making promo and catalog. This system was built using Microsoft Visual Basic.Net and database Microsoft Access. This system can be used as a solution for company to make prediction of customer habits by type and target customer market, that can be help the company to increasce corporate image and profit the company. This study used best testing rule with minimum support 30% and minimum confidence 50%.Keywords : ARM, combination, digital printing, itemset, rule, minimum support, minimum confidence, prediction.