CLUSTERING OF UNDERGRADUATE STUDY PROGRAMS BASED ON ALUMNI’S WORK FIELDS USING ITB TRACER STUDY DATA 2013-2015

• Main Author: Johannes Aneky, Steven
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/73010
• Institution: Institut Teknologi Bandung

In this final project, unsupervised learning methods are used, first, to group (cluster) undergraduate study programs based on their fields of work, and second to group fields of work for each undergraduate study program. The methods used are the K-Means Clustering and Fuzzy C-Means Clustering, and the data is taken from the ITB tracer study for batch 2013-2015. Since a choice of work field for an alumni of a study program should be quite flexible, then, beside the K-Means Clustering, the Fuzzy C-Means Clustering method will also be used to solve the first problem by introducing its membership degree. While, the K-Means Clustering method will be sufficient to solve the second problem. Both methods have been able to group undergraduate programs based on their fields of work and to group fields of work for each undergraduate program.