Peramalan Jumlah Penerimaan Siswa Baru Menggunakan Metode Exponential Smoothing - Kelvin Rainey Salim; Noveri Lysbetti Marpaung (Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains, 2020)
The need for rapid technological development, especially in the field of education. Many aspects are worth considering in the world of education, one of which is prediction, which is considered capable of overcoming one of the problems in the world of education, namely fluctuations in new students. This fluctuation will be related to school policies later. The Single Exponential Smoothing method is used to determine predictions of student acceptance in the next academic year period. Exponential Smoothing method is a pretty good forecasting method for long and medium term forecasting. This method is also able to handle students' irregular fluctuations. The data to be processed is the number of student admissions for the period 1999/2000 to 2003/2004 The results obtained from this study are the results of the analysis of the Single Exponential Method to obtain information about the prediction of new student admissions and the level of accuracy with MAPE for the next school year for 4 years. Forecasting results can be influenced by several factors such as construction of facilities and others. Forecasting results using the Single Exponential Smoothing Method can predict the number of new students in the Academic Year 2003/2004 is 117 people, whereas the number of students accepted reach 125 people. It means that MAPE of forecasting with Exponential Smoothing Method can reach 6.4%. This is the smallest percentage of error (MAPE) in this research. The smallest number of students accepted in the Academic Year 2000/2001, where the number of students accepted was 47 people and students were predicted as many as 26 people. MAPE produced this year is 45%. Keywords: New Student Data, Forecasting Data, Single Exponential Smoothing Method, Mean Absolute Percentage Error (MAPE)