Classification Of Mobile Phone Purchases Based On Sales Transaction Data Using The Rule Based Reasoning

Abstract

Ordering goods to mobile distributors randomly without classifying the items that are in great demand by consumers is certainly very detrimental because it greatly affects the sale of goods, The solution to make it easier for shop owners to place orders to distributors in terms of selecting the type of goods that consumers are very interested in is by using an application using the method Rule Base Reasoning based on transaction data that has been done. Rule Base Reasoning is an expert system based on a set of rules that represent human knowledge and experience in solving complex cases and imitating human ability to make decisions and solve problems. Test results of the most sold cellphones are A12 as much as 97%, A1K 67%, Rodmin 8 Apro 53 and others ranging from 3% to 30%, Searching for similarity values ​​is enough to do for cases that have the same index as the new case, This system only stored in the database that has been provided and the input data received by the system is still limited.