Abstract
Intellectual Capital (IC) is one type of capital which is known as an intangible asset of an organization. Therefore, IC is claimed to be a valuable asset in the organization. However, the study of IC was not widely conducted in Thailand. IC includes human capital, structural capital and customer capital. This paper applies data mining techniques, classification algorithms for generating IC model of organizations in Thailand. Three candidate classification algorithms including Decision tree (ID3), Decision Tree (C4.5) and Bayesian Network were compared for the prediction powers in this study. Data set was obtained form a survey of 216 organizations located in the central part of Thailand. Results show that Bayesian Network has the highest prediction power. The accuracy of this IC model is about 83% which is good. The implication of this model is also suggested.