Graduates Profile Mapping based on Job Vacancy Information Clustering

Nowadays, an industry’s expectation that’s often not fulfilled by job applicants require companies to actively cooperate with universities, one of the reasons is through employees that is considered to have good performance to find talents within their alma mater. This research aims to analyze job vacancy information uploaded by graduates for juniors in their university that can be mapped into a graduate’s profile and evaluation materials in making a curriculum. Collected job vacancy information from several communication media are generally unstructured data which requires it to be preprocessed first through a data mining convention to produce several terms ready to be processed, continued with implementation of TF-IDF, feature extraction using PCA, and grouping using k-Means algorithm. The clustering analysis found 3 job clusters i.e. developer, teacher and researcher/lecturer as job vacancies that frequently shared by graduates. This result obtained from clustering analysis using 10 words as a minimum document frequency based on Elbow Method and Silhouette Coefficient analysis.