Wound Up Malaysian Companies' Pattern Exploration Using Data Mining Methods

Suhaila Zainudin, Abdul Razak Hamdan, Zainol Aini Mohamed, Nor Idayu Ahmad Shukri
dx.doi.org/10.17576/apjitm-2015-0402-07

Abstract

A company is wound up when the company is unable to pay financial debts or is experiencing serious financial distress. From the year 1998 until 2003, an average of 1166 companies were wound up yearly. This research focuses on the knowledge exploration of wound up companies in Malaysia using association rules mining techniques (quantitative) and the involvement of domain expert in knowledge evaluation (qualitative). Association Rules Mining technique is used to mine the implicit patterns of wound up companies by analyzing relationships between attributes such as total asset, total liability and profit and loss. The human expert functions to verify the significant relation between attributes and the mined patterns. This research succeeded to mine 2 quantitative criteria and 9 qualitative criteria related to wound up companies. The criteria combination can be utilized for evaluating the risk of wound up Malaysian companies in the future.

keyword

association rules mining, data mining, domain knowledge, wound up company

Area

Data Mining and Optimization