| Abstrak/Abstract |
—Currently, the common method to predict
personality implicitly (Implicit Personality Elicitation) is
Personality Elicitation from Text (PET). PET predicts
personality implicitly based on statuses written on social media.
The weakness of this method when applied to a recommender
system is the requirement to have minimal one social media
account. A user without such qualification cannot use such
system. To overcome this shortcoming, a new method to predict
personality implicitly based on demographic data is proposed.
This proposal is based on findings by previous researchers
stating that there is a correlation between demographic data and
personality trait. To predict personality based on demographic
data, a personality model (rule) is needed. This model correlates
demographic data and personality. To apply this model to a
recommender system, another model is needed, that is preference
model which connects personality and preference. These two
models are then applied to a personality-based recommender
system for fashion. From performance evaluation, the precision
of and user satisfaction to the recommendation is 60.19% and
87.50%, respectively. When compared to precision and user
satisfaction of PET-based recommender system (which are 82%
and 79%, respectively), the precision of demographic data-based
recommender system is lower whereas the satisfaction is higher. |
