Multi attribute decision making model using multi rough set: Case study classification of anger intensity of Javanese woman

Decision-making process typically involves multiple attributes. It is using a part or whole attributes to find the best decision from the alternatives. Some methods such as rough set are used to solve this problem but it has worse time complexity with respect to the numerous attributes. Hence, Multi Rough Set is proposed to improve the performance of rough set. In this study, this method used to classify the anger of Javanese woman's which require numerous attributes but has limited number of object. We divided the information table into several groups which has similarity attribute and it is computed simultaneously. The decision of each group as result of rough set and then used fuzzy rule set to obtain the final result. Using leave one out cross validation obtained 79% more accurate than using single rough set for all attribute.