APPLICATION OF LAPTOP RECOMMENDED DATA MINING FOR STUDENTS USING APRIORI METHOD - Ayu Rahma, Fachira; Prihatin, Titin (Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta, 2023)
This study aims to analyze laptop recommendations for students so that students can buy laptops according to affordable prices and desired specifications. The method used is the Apriori Algorithm Method with a minimum support of 15% and a minimum confidence of 50%. This research was conducted to find out laptops with good performance and affordable prices that can be used as recommendations, especially students who work part-time. The data obtained for this study, namely data downloaded from the Kaggle platform for 1 year and looking for supporting references (such as books and journals). The results of this study show that there are laptops that are recommended by laptop sellers so that they are purchased by consumers significantly. Based on a priori analysis, laptops were found that can be used for recommendations using association rules, namely Apple with a support value of 35%, HP with a support value of 26%, Dell and Razer with a support value of 19%. If Apple and HP are purchased simultaneously it has a confidence value of 45%.