Outlier Detection Using Association Rule Mining for Information Quality Improvement
2017
The abundance of data production in the latest decade encourages researchers to create a variety of opportunities.This shall be interspersed with the strong willing of the society to change their perspective regarding the availability of data.Once data viewed as a dull stack of letters and numbers, they must now be considered as a fresh resource capable of contributing values and benefits for the owners.Good data will produce high-quality information, which then will direct to a good decision-making.One of the efforts to improve data quality is by performing an outlier detection.There are few methods to do that, but none is considered the best knowing each retains its own strength when applied to different cases.Therefore, this research aims at proving the capability of Association Rule Mining method in detecting outlier when applied to a case requiring interpersonal relationship definition.