Implementasi Autoregressive Integrated Moving Average Untuk Prediksi Calon Mahasiswa Baru Universitas Katolik Musi Charitas

Febriant, Frando (2024) Implementasi Autoregressive Integrated Moving Average Untuk Prediksi Calon Mahasiswa Baru Universitas Katolik Musi Charitas. Undergraduate thesis, Universitas Katolik Musi Charitas.

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Abstract

Predicting the number of prospective students is an important aspect for universities in planning capacity and resources. The accuracy of this prediction allows universities to make more informed and optimal decisions regarding student admissions. This study aims to determine the use of the Autoregressive Integrated Moving Average (ARIMA) model in predicting the number of new student candidates at Musi Charitas Catholic University. The ARIMA model is applied to a dataset of new student admissions from the academic year 2018/2019 to 2022/2023. The analysis process begins with model identification, parameter estimation, diagnostic testing, and forecasting. The results of the analysis process show that the ARIMA(2,0,2) model is the most optimal model for this data. Model diagnostic tests were conducted using two main metrics namely, Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). The resulting model achieved an RMSE value of 0.663 and a MAPE of 0.155, indicating a prediction accuracy of 15.5%. The prediction results show an increase in the 2023/2024 academic year, namely 983 new student candidates and a decrease in the 2024/2025 academic year, namely 897 new student candidates, and a decrease again in the 2025/2026 academic year, namely 813 new student candidates.

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