<![CDATA[Abstract - Students is important component in an educational institution, new students who enroll in Cepu Oil and Gas Vocational School in 2012 were 475, in 2013 were 526, in 2014 were 687, in 2015 were 785, 2016 were 648, and in 2017 were 461. New students who register has increases and decreases for every year, it caused changes any policies taken by the school principal to optimize the provision of facilities and teaching force.The new student acceptance prediction is needed to support decision making and policy planning in the future, therefore the authors conducted a study to predict new student admissions based on the time series data obtained from Cepu Oil and Gas Majority High School in the form of prediction applications using the Adaptive Neuro algorithm Fuzzy Inference System (ANFIS) which is processed using matlab. Predictive error value of manual calculation is calculated using MAPE method (Mean Absolute Percentage Error) and prediction error calculation with prediction application is calculated using the MAPE and RMSE methods (Root Mean Squared Errors).The results of this researches is the number of new students who enrolled in 2018 is 607,327 with a percent error value of 0.00333682% calculated using the MAPE method and the average error of 0.151786 was calculated using the RMSE method. Predicted results can be used as references in supporting decision making by the Cepu Oil and Gas Vocational High School Principal.Keywords: Application, Prediction, Adaptive Neuro Fuzzy Inference System, Time-series Data. ]]>
Copyrights © 2020
