Data Mining Untuk Mengetahui Tingkat Loyalitas Konsumen Terhadap Merek Kendaraan Bermotor dan Pola Kecelakaan Lalulintas di DIY
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.
Penulis: Agus Sasmito
Ariwibowo, Edi Winarko
Kode Jurnal: jptinformatikadd110167
