Analisis Prediksi Pemilihan Mata Kuliah Peminatan pada Jurusan Teknik Informatika Universitas Indo Global Mandiri Menggunakan Metode Linier Regresi

Abstract

Universitas Indo Global Mandiri (UIGM) in Palembang organizes various higher education programs, from diplomas to PhDs. In this study, we perform data analysis using linear regression methods and predictive modeling techniques. In this connection, a survey was conducted among UIGM Computer Science Engineering course students to collect the necessary data. Data generated from surveys is used to predict future student choices when choosing a course of study. According to the forecast results, 12 students choose Intelligent Computer and Vision (KCV) majors, and 84 students choose Software Engineering (RPL) majors. Due to data limitations, these predictions may not be completely accurate. However, more complete data can help improve prediction accuracy. Therefore, it is important to collect more complete and representative data to improve prediction accuracy. The more complete the data, the more accurate the forecast results, which can provide more precise guidance in decision-making about your area of ​​expertise. This study contributes to the application of linear regression and predictive modeling techniques in higher education and highlights the importance of comprehensive data collection to support better predictive outcomes.