Enhancing ARIMA Model Accuracy for New Master's Student Enrolment Forecasting at Hasanuddin University Through External Variable Engineering

Muh. Arief Wicaksono, Ady Wahyudi Paundu, Muhammad Niswar

2025

Abstract

Accurate forecasting of new student enrolment is crucial for effective management and strategic planning in higher education institutions. This research examines the integration of engineered external variables into the ARIMAX model to improve the accuracy of forecasting new master’s (S2) student admissions at Hasanuddin University. The study utilizes applicant data from 2019/2020 to 2024/2025, applying hierarchical mode imputation to address missing values and Spearman correlation for external variable selection. The results show that while “Father’s Occupation” has the highest correlation with enrolment numbers, “Mother’s Education” as an external variable yields the lowest prediction error with a MAPE of 13.21%. These findings highlight the importance of empirical model validation using MAPE rather than relying solely on correlation analysis. The approach proposed in this study provides practical insights for university policy makers in planning student admissions based on robust, data-driven forecasts.

Paper Citation

in Harvard Style

Wicaksono M., Wahyudi Paundu A. and Niswar M. (2025). Enhancing ARIMA Model Accuracy for New Master's Student Enrolment Forecasting at Hasanuddin University Through External Variable Engineering. In Proceedings of the 1st International Conference on Research and Innovations in Information and Engineering Technology - Volume 1: RITECH; ISBN 978-989-758-784-9, SciTePress, pages 189-195. DOI: 10.5220/0014265900004928

in Bibtex Style

@conference{ritech25,
author={Muh. Arief Wicaksono and Ady Wahyudi Paundu and Muhammad Niswar},
title={Enhancing ARIMA Model Accuracy for New Master's Student Enrolment Forecasting at Hasanuddin University Through External Variable Engineering},
booktitle={Proceedings of the 1st International Conference on Research and Innovations in Information and Engineering Technology - Volume 1: RITECH},
year={2025},
pages={189-195},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0014265900004928},
isbn={978-989-758-784-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Innovations in Information and Engineering Technology - Volume 1: RITECH
TI - Enhancing ARIMA Model Accuracy for New Master's Student Enrolment Forecasting at Hasanuddin University Through External Variable Engineering
SN - 978-989-758-784-9
AU - Wicaksono M.
AU - Wahyudi Paundu A.
AU - Niswar M.
PY - 2025
SP - 189
EP - 195
DO - 10.5220/0014265900004928
PB - SciTePress