VENDOR RATE SELECTION SYSTEM APPLIED WITH DATA MINING

In business world, making a good and correct decision is essential but for a person
alone to make the decision, the result will be incorrect as human being will include
their emotion while making the decision. In order to fix this problem, a business
system that fully utilized their previous business's data and pattern should be
developed. The scope of this report is to give an overview about how this system
being developed and worked provided with some related research and discussion. In
this project, it will use data mining technique in order to fmd the most suitable
logistics vendor to be used in a company. In order to get the pattern, there are several
factors that will be considered for examples the rate given, destination, services
provided and etc. The main objective of this project is to analyze past vendor's data
set from a company by using data mining technique, thus, it will help the user to
make a better decision. By using the technique, the set of data will be group into
vendor's company classes and the most frequent vendor that has been used before
will be selected and the system will prompt the user. The methodology used in this
project is Extreme Programming (XP) methodology because there are many
advantages such as this methodology can apply to changes. This project will help a
collaboration company to improve their decision making and business performance.