Study of Muslims in marital system using markov chain simple exponential smoothing (MCses) technique

The Markov Chain (MC) model is a popular mathematical model used to observe the flow of data in a system. It can also be used to forecast future values for short-term period. However, most previous studies do not focus on the accuracy of the forecast values. Integration of the MC model and Simple Moving Average (SMA) technique is known to produce higher forecast accuracy than the classical MC model for the
case of long-term projection with known previous data. However, Simple Exponential Smoothing (SES) technique is more flexible than SMA because it uses a smoothing constant. Therefore, this study develops modeling steps for MC model in the case of limited data and short-term projection by integrating MC model with SES
(MCsEs). The MCsEs hybrid model is used to enhance the MC model and improve the accuracy of the forecast values. Four error measures used to determine the accuracy of this model are mean absolute deviation, mean absolute percentage
deviation, mean absolute percentage error and mean square error. This study uses a sample of 6061 Muslim couples data in Pendang, Kedah who are in the marital system for the year 2013 and 2014. The number of Muslims in subsequence year
according to gender and age categories is forecasted using proposed MCsEs hybrid model. Comparison with MC and MCsMA models indicates that the developed MCsEs hybrid model has better forecast accuracy. Therefore, the MCsEs hybrid model is the most appropriate model to forecast the number of Muslims in the marital system
according to gender and age categories for the year 2014. This model can be used for short-term projection in cases with limited data and is applicable in various fields.