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Research Background

In terms of making decision to purchase a car, many aspects need to be considered. However, selecting a suitable car is often done in an unplanned manner. Making decision in purchasing a car is an important aspect since a lot of criteria needs to be taken into account. Currently, there are a lot of specification would be demanded by car buyers to purchase their  dream car. This sort of decision have a major impact in their life. Customers will satisfied if they purchase their car rightly that includes their  budget and they will feel frustrated and get a little stress if they purchase wrong car. Therefore, in order for them to make a  right decision there should be a system to generate suitable car  that will help them in making decision and give pre-liminary idea to them when they want to purchase a car. The system will take into account their demographic factors such as income, work and also specification of car that demanded by the customer. This research  will demostrates the use of rule-based classification to suggest suitable car to car’s buyer. The scope involved in this study were the automobile company for PROTON also the customers.

Data mining involves the exploration and analysis of large databases to find patterns and valuable information that can aid in decision making. This research used the rule-based classification to recommend suitable car to customers. In rule-based classification, group documents together, decide on categories, and formulate the rules that define those categories; these rules are actually query phrases. Then index the rules and use the MATCHES operator to classify documents. This research illustrates the use of data mining approach to build predictive pattern for predicting customer's intent of purchasing car.