Analisis Prediksi Jumlah Mahasiswa Universitas Harapan Medan Menggunakan Metode Least Square - Asih, Munjiat Setiani; Hasibuan, Ade Zulkarnain (Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA), 2023)
Increasing the number of students in tertiary institutions is the main focus for university administrators in planning development strategies and better educational services. Predicting future student numbers is important in the context of long-term planning and strategic decision making in higher education institutions. This research aims to predict the number of students at Harapan University, Medan in 2024 based on historical data from 2017 to 2023 using the least squares method. The least squares prediction method is used to fit a linear regression model that connects the independent variable (year) with the dependent variable (number of students). Historical data on the number of students over a specified time period is used to develop an accurate forecasting model. The research results show that based on the least squares model adjusted to historical data, the increase in the number of students at Harapan Medan University is projected to be 14.17% in 2024. The results of this prediction provide valuable insight for university managers in planning and implementing promotional strategies, resource allocation , and plans for new student admissions. By better understanding student growth trends, universitiescan improve operational efficiency, optimize academic and administrative services, and strengthen their position in the higher education market. This research has important implications for higher education management in the context of strategic planning and development of educational institutions.