Ukuran Akurasi Model Deret Waktu Manajemen Informasi Kesehatan PERTEMUAN 13 Mieke Nurmalasari Manajemen Informasi Kesehatan
Kemampuan Akhir Yang Diharapkan Mahasiswa mampu memilih model terbaik dengan melihat ukuran akurasi model Mempelajari berbagai ukuran keakuratan model, yaitu: MAD, MAPE dan MSE
What is MAD, MAPE and MSE? Use the MAPE, MAD, and MSD statistics to compare the fits of different forecasting and smoothing methods. These statistics are not very informative by themselves, but you can use them to compare the fits obtained by using different methods. For all three measures, smaller values usually indicate a better fitting model.
Time Series Forecasting Process Look at the data (Scattr Plot) Forecast using one or more techniques Evaluate the technique and pick the best one
Evaluation of Forecasting Model BIAS - The arithmetic mean of the errors n is the number of forecast errors Excel: =AVERAGE(error range) Mean Absolute Deviation - MAD No direct Excel function to calculate MAD
Evaluation of Forecasting Model Mean Square Error - MSE Excel: =SUMSQ(error range)/COUNT(error range) Standard error is square root of MSE Mean Absolute Percentage Error - MAPE R2 - only for curve fitting model such as regression In general, the lower the error measure (BIAS, MAD, MSE) or the higher the R2, the better the forecasting model