Pattern discovery of Indonesian customers in an online shop: A case of fashion online shop

The amount of information displayed on an online shop could distract consumers' focus that might result in customers leaving the website or canceling transaction. Recommendation that provides customers with relevant products is required to make a decision easy for a wide variety of products. Relevancy of products for a customer can be achieved through user patterns discovery. This study aims to develop a user model to provide personalization on e-commerce based on customers group. This study involved 100 participants consisted of 25 girls, 25 adult females, 25 boys, and 25 adult males. Data collection was performed using an e-commerce website i.e. http://www.erstore.biz to record users' activity. Data analysis was done using the RapidMiner Studio 5 to provide a decision tree as user model grouped by age and gender. This study found that male and female users among different age groups have different patterns in recognizing process. Female users have a shorter process in the identification of age group than male users.