Seaweed drying characterization via serial statistical criteria analysis

In drying seaweeds, it is important to describe its behavior using semi-theoretical models. Predicting the best model for seaweed was commonly done by testing goodness of curve models calculating coefficient determination R2, reduced chi square X2, root means error (RMSE) and mean bias (MBE). However, essential rank before selection assessing performance index Φ relative deviation (MRD). It also necessary test normality evaluating skewness kurtosis statistics D' Agostino Pearson which fit. The simple sample run confidence interval must be satisfied These are conditions that should met under serial statistical criteria analysis. This study utilized choose seaweeds. Employing this analysis used models, Modified Page emerged as depicts seaweeds with accuracy 99.98% highest 452.1967.