MODEL DESIGN FOR ANALYZING CUSTOMER PREFERENCE TOWARDS HEELED SHOES DESIGN OF ADORABLE PROJECTS
In order to survive in dynamic markets, Adorable Projects launches new product nearly every month. During the new product development process, designers use their intuition in analyzing the customers’ abstract preference. This causes a huge mental load, resulting a design without proper data-driv...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/39723 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | In order to survive in dynamic markets, Adorable Projects launches new product
nearly every month. During the new product development process, designers use
their intuition in analyzing the customers’ abstract preference. This causes a huge
mental load, resulting a design without proper data-driven information.
Incompatibility between product design and customer preference will lead to
inefficiency of time and resources. Therefore, the aim of this research is to develop
a method for customer preference analysis and an application made to facilitate
the model execution and results representation.
Fuzzy association rule mining is used to discover relationships between product
attributes and salability of heeled shoes. Binary particle swarm optimization and
genetic algorithm substitute traditional algorithms that require support and
confidence threshold. Comparison between the two algorithms shows that genetic
algorithm outperforms binary particle swarm optimization with model validation
of 80,4%. Afterwards, an application prototype is developed based on the chosen
model. This application utilizes Microsoft Excel and R. Verification analysis shows
that the application satisfies Adorable Projects’ needs in analyzing customer
preference. |
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