Prediksi Jumlah Mahasiswa Baru Fti Usn Kolaka Menggunakan Metode Single Exponential Smoothing
DOI:
https://doi.org/10.54259/satesi.v3i1.1573Keywords:
Predicton, Number of Students, Single Exponential Smoothing, MAPEAbstract
The FTI student admission target every year is often not achieved. This happened because of the change in FTI's location, from USN Kolaka which was in Kolaka to USN Kolaka which was in Tanggetada. In addition, there are also other causes in terms of the large number of students who do not graduate on time, causing an unbalanced ratio of lecturers and students. This will reduce the assessment at the time of accreditation. Predictions are made to assist FTI in planning and making decisions to determine priorities for how many prospective students will be accepted each year. The observational data used are data on the number of new FTI students for the 2013-2021 academic year (9 periods) for the Information Systems study program and the 2018-2021 academic year (4 periods) for the Computer Science study program. Data processing is carried out using the Single Exponential Smoothing Method and MAPE (Mean Absolute Percent Error) accuracy testing. The results of testing this method are that for the information systems study program the predicted results obtained in the 2022/2023 academic year are 141 people, and the smallest value of MAPE = 26.67% which shows the ability of the forecasting model to be quite good (Reasonable). Meanwhile, for the computer science study program, the prediction results obtained in the 2022/2023 academic year were 116 people, and the smallest value of MAPE = 18.52%, which indicates a good forecasting model ability.
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