Open AccessPenerapan Data Mining Korelasi Penjualan Spare Part Mobil Menggunakan Metode Algoritma Apriori (Studi Kasus: CV. Citra Kencana Mobil)
Author(s) -
Amenta Ovilianda Br Ginting
Publication year - 2021
Publication title -
journal of information and technology
Language(s) - English
Resource type - Journals
ISSN - 2775-2720
DOI - 10.32938/jitu.v1i2.1472
Subject(s) - spare part , database transaction , computer science , database , apriori algorithm , association rule learning , data mining , operations research , operations management , engineering
By utilizing customer data that has been stored in the database, the management can find out how the current sales system is less efficient, therefore a system is needed to process information data more quickly and accurately in increasing sales of car spare parts using the Data Mining application. The Apriori Algorithm method that works by searching for and finding associated patterns among the products being marketed, so that later it can help companies improve the associated items. And with the sales transaction data, the company can know better how they should increase the spare part stock in the company. From the results of testing the sale of car spare parts with 589 data, it was found that 81 rules were formed and the highest Best Rule was obtained and a minimum support value of 1% and a confidence value of 11% If the type of car is Avanza / Xenia and the brand is Toyota, the spare parts used are filters. Air. With supporting spare parts in the database of 1% and certainty of spare parts of 11.