Identification Of Higher Education Student’s Entrepreneurial Motivation Using Fuzzy CMeans Algorithm

The purpose of this research is to identify student entrepreneurial motivation in higher education using Fuzzy C-Means Algorithm. The entrepreneurial motivation was predicted based on the perception of the career attractiveness and feasibility level to start a business. The instrument uses a questionnaire consisting of two types of statements, fourteen statements of career attractiveness, and eleven statements of feasibility. This research used the Fuzzy C-Means algorithm to identify the entrepreneurial motivation into two categories, highly and lowlily motivated. Fuzzy C-Means algorithm is a data clustering method where each data into a cluster determined by the degree of membership. The Fuzzy C-Means algorithm is iterative and required ten iterations to converge onto a stable solution. The finding of this research is the Fuzzy C-Means algorithm able to identify higher education student’s entrepreneurial motivation. The number of students who low motivated is a very slight difference from students who high motivated. Entrepreneurial motivation is essential for students to open up opportunities to start a business in the future.