Telkom Univ Waiting Time Analysis: SVM vs. Logistic Regression with Tracer Study Data of 2022

University is an educational degree that is required to prepare and enable aspiring graduates to be able to participate and compete in the industries. Alumni tracking or tracer study is needed to see the quality of a graduate to improve and evaluate a university. Classification of the waiting time for work aims to determine the level of smoothness of graduates or alumni in getting a job. In this study, a classification analysis was carried out from the data of the Telkom University Tracer Study in 2022 using the Support Vector Machine (SVM) and logistic regression algorithm methods. The methods are chosen because SVM and logistic regression can make a good classification among the binary classes such as ’fast’ and ’slow’. This study also investigated the most significant factors among the competencies possessed by students upon graduation regarding the waiting time focusing on the most influential factors affecting graduates’ waiting times to enter the workforce. This can guide the university to prepare students better. Three influential factors were compared with all seven competency factors for classification. After being classified the best result is to use seven features with logistic regression achieved an accuracy of 82.11% and SVM achieved an accuracy of 88.15%.