Design of expert system for owning motorcycle with Naive Bayes classifier

Abstract

Nowadays, motorcycle is widely used by many people. There are several major categories of motorcycles in Indonesia such as automatic gear (matic), moped, and sport. Each motorcycle has a lot of types; even each type may be divided into several sub types. Generally, a sub-type of motorcycle is distinguished by features and spare parts that determine the sales price of motorcycle. Therefore, customers have trouble to determine the type of motorcycle that suits their needs and wishes. This article proposes a model that helps customer decide the motorcycle in accordance with the following criteria: gender, occupation, income, and age. This model compares and calculates a new customer with many previous customers with Naive Bayes Classifier. In evaluation phase, this model shows that 89.12% of customers feel satisfied. It means that this method valuable implement on this model. In further work, customer's advance criteria like color, durability, and resale price should increase the customer's satisfaction.