Prediction for Total Number of Lab Participants by Fuzzy Time Series Method (case Study: Information Engineering of Bhayangkara Surabaya University ) - Febriardi Mahendra; Rifki Fahrial Zainal; Syariful Alim (JEECS (Journal of Electrical Engineering and Computer Sciences), 2017)
Forecasting is a way to estimate a future value with using past data. One method of forecasting is the fuzzy methodtime series. The purpose of this study is to predict the number of students practitioners follow Department ofInformatics University Bhayangkara Surabaya by using fuzzy method time series. The created app can be used topredict the next 1 year. If the actual data in the year predicted inputted, the application can predict the next yearagain. The prediction error rate is calculated using Mean Absolute Percentage Error (MAPE). From the test resultsin predicting the number of students followers 7 courses Practicum Informatics Engineering Bhayangkara Universityof Surabaya in 2010-2012 using the method proposed in this thesis for practicum PTI obtained MAPE value of20.50%, Practical ANP obtained MAPE value of 0.50%, Network Computer practicum obtained MAPE value at8.50%, practicum Database obtained MAPE value of 0.50%,Managemen Network Computer practicum obtainedMAPE value of 14.50%, practicum PKG obtained MAPE value of 0.84% and practicum PBO obtained MAPE valueof 0.21%. Based on the results of testing the data it can be concluded that the fuzzy time series method when used onmore data many, it will get the accuracy of better and precise forecasting values.