IMPLEMENTATION OF FORECASTING EXPONENTIAL SMOOTHING IN THE NUMBER OF NEW STUDENT PREDICTION INFORMATION SYSTEM AT SMK AL MA'SHUM

Abstract

SMK Al Ma'shum annually conducts socialization and promotions in junior high schools. Prediction of the number of prospective new students is one of the most important things in the evaluation process or high cognitive at SMK Al Ma'shum. This serves to determine the priority of how many prospective students will be accepted, where the number of students sometimes tends to decrease and increase. This makes the school must try to estimate the number of new students from each of these majors next year will increase or decrease. If this is not done by the school, it will have an impact on the operational costs of the school. The goal is to predict the number of prospective new students who will be accepted at the Al Ma'shum Vocational School next year using the forecasting exponential smoothing method. The prediction system for new students at the Al Ma'shum Vocational School uses the PHP and MySQL programming languages ​​to help the forecasting process be fast and accurate. The prediction results for 2022 are accounting majors as many as 19.23 new students with MAPE 20.52%, computer and network engineering majors as many as 102.73 new students with MAPE 9.12% and motorcycle engineering majors as many as 76 new students with MAPE 25.53 %. So it can be concluded that the forecasting exponential smoothing method can help predict new students at SMK Al Ma'shum.