Applying Data Mining to Analysis of Mismatch Between Education and Labor Market in Indonesia

Abstract

One of the labor problems in Indonesia is the occurrence of mismatch (incompatibility between education and job). The incompatibility of education and job (labor market) can be categorized into several criteria such as vertical mismatch, horizontal mismatch, overqualification, under qualification, over skilling, under skilling, credentialism and economic skills. In several countries, analysis of mismatch between education and labor market can be used with several methods such as the Maximum Likelihood equation, the Mincer-type income equation, and the use of clustering algorithms in data mining. Indonesia can adopt a method of measuring the mismatch between education and labor market which suitable with the condition in Indonesia. The use of the K-Means algorithm or the hierarchical clustering algorithm will be able to see how much mismatch is occurring in Indonesia. Clustering is carried out referring to the Republic of Indonesia’s Presidential Regulation No. 8/2012 and the Indonesian Classification of Work (KBJI).