Pelatihan dan Pendampingan Penggunaan Sistem Prediksi Kelulusan Mahasiswa dengan Fuzzy C-Means

Abstract

The problem of low on-time graduation rates in private universities is a major challenge in academic management and institutional accreditation processes. This service activity aims to provide training and assistance to academic managers at Bumigora University in the use of a student graduation prediction system based on the Fuzzy C-Means method. This activity includes training in the use of data mining, understanding algorithms, and implementation using the Python programming language. This service activity includes four stages: (1) identification of partners and needs, namely academic management personnel of Bumigora University who need a graduation prediction system and data analysis skills; (2) training and workshops on data mining, Fuzzy C-Means, and CRISP-DM with hands-on practice using Python; (3) system implementation through simulation of student graduation prediction; and (4) evaluation through pre-test, post-test, and reflective discussion. All stages are integrated to improve the capacity of academic management. The results showed an increase in participants' understanding and ability to operate the system to predict student graduation. This system is expected to help the academic monitoring process more effectively and data-based.