Data Mining Untuk Mengetahui Loyalitas Konsumen Terhadap Merek Kendaraan Bermotor dan Pola Kecelakaan Lalulintas

Aribowo, A. Sasmito and Winarko, Edi Data Mining Untuk Mengetahui Loyalitas Konsumen Terhadap Merek Kendaraan Bermotor dan Pola Kecelakaan Lalulintas. INDONESIAN JOURNAL OF COMPUTER AND CYBERNETIC SYSTEMS. ISSN 1978-1520

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    Abstract

    The data of vehicle sales and traffic accident can be processed into information that is important for vehicle dealers and the Police Department. Those important information researched are the level of consumer loyalty to the vehicle brands and to predict the vehicle’s brands that will be purchased by a consumer. The study also tries to analyze the traffic accident data to find out is there any link between the occurrence of an accident to a certain brand of vehicle. This research implementing data mining method called ‘rule based classification’ to establish the sales of vehicles rules by which can be used to classify consumer into group level of brand loyalty and also estimate the brand of the next vehicle’s brand that will be purchased by the consumer. This research will process the data traffic accident by using data mining techniques called Apriori Method. Apriori Method is used to identify a pattern of accidents based on brand, type of vehicles, and the vehicle’s color. The results are used to estimate whether there is any correlation between the occurrences of a traffic accident to a particular brand. The result can help companies or vehicle dealers to obtain information about the level of the consumer’s brand loyalty to the dealer’s brand and to predict the brand that the consumer would be buy for the next vehicle. The result can also help the Police Department to find out whether there is any correlation between the occurrence of traffic accidents to the brand, type and the color of vehicle. Keywords— rule based classification, apriori, brand loyalty, traffic accident

    Item Type: Article
    Subjects: 000 Komputer, Informasi, dan Referensi Umum
    500 Sains dan Matematika
    Divisions: Fakultas Teknologi Industri > Teknik Informatika
    Depositing User: H Hidayatullah Himawan
    Date Deposited: 22 Oct 2013 16:58
    Last Modified: 22 Oct 2013 16:58
    URI: http://repository.upnyk.ac.id/id/eprint/7477

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