Forecasting University Admissions through Student Achievement using Arima Method - Maslamah, Siti; Aripriharta; Handayani , Anik Nur; Horng, Gwo-Jiun (Universitas Pendidikan Ganesha, 2025)
Education is a means that allows individuals to develop their potential through the learning process. Vocational High School (SMK) is a formal education that prepares students to become middle-level workers, enterpreneurs, or continue to college. The admission system for State Universities (PTN) is divided into three pathways: SNBP, SNBT, and Independent Selection. This study aims to forecast new student admissions through the achievement pathway, specifically based on report card grades, with a case study at vocational school. The forecasting method used is the Autoregressive Integrated Moving Average (ARIMA), by analyzing the trend of student grades data admitted to state universities in 2020-2023, which includes report card grades from semesters 1 to 5. From the ARIMA analysis that was carried out for student admissions at state universities, the best ARIMA model was obtained (1,1,2) with an average MAPE error value of 2.12%. This indicates that the ARIMA model has good performance and can be used to forecast new student admissions to state universities. This research is expected to provide recommendations to educational institutions for better planning in student assessments, thereby increasing the probability of students being admitted to state universities.