Penerapan Metode Support Vector Machine (SVM) untuk Memprediksi Pemilihan Karir bagi Alumni UMSIDA - Qur'ani, Meisyilia Difanada; Setiawan, Hamzah; Kautsar, Irwan Alnarus (JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika), 2025)
The success of a university is not only determined by its educational process but also by the ability of its graduates to get a job. The aim of this research is to develop and evaluate a predictive model using the Support Vector Machine (SVM) method to predict career choices for alumni of the Muhammadiyah University of Sidoarjo (UMSIDA) . This research uses a quantitative approach, in the topic of predicting sample data obtained from tracer data of Umsida students which is compiled into the title "Application of the Support Vector Machine (SVM) Method to Predict Career Choices for UMSIDA Alumni". The model evaluation results show that SVM has very good performance, with high precision, recall and f1-score for the dominant class. Feature importance analysis shows key features that have a significant influence on model decisions, providing valuable insight into the factors that influence alumni career choices. With an overall accuracy of 97%, this model is able to provide appropriate career recommendations for the majority of alumni.