Papers by Voni Apriana Dewi Dewi
There are some studies on poverty levels have been introduced. One model that is often used is li... more There are some studies on poverty levels have been introduced. One model that is often used is linear regression. However, this linear regression has several limitations, including the regression model requires that the independent variables do not occur multicollinearity, the data must be normally distributed, it is difficult to interpret the intercept coefficient and result in an interpretation that is not in accordance with the actual conditions. Based on these conditions, the writer are interested in using the new model rough sets to a quartile based criteria division. In the model of rough sets, the data elimination (reduction) stage is performed so that fewer rules and easy to understand rules can be obtained. The results of this study is indicate that the accuracy of the rough sets model is greater than multiple linear regression. In other words, the recommended rough sets model can be used as one model because it does not depend on assumptions as in the regression model.
The conventional regression model is widely used to explain the mathematical relationship between... more The conventional regression model is widely used to explain the mathematical relationship between exogenous and endogenous variables. This model is also capable for prediction and planning purposes. However, to achieve the high prediction accuracy is not easy task by using this model, especially for categorical data type, because fully uncertainty, volatility and unpredictable during data collection. Moreover, the data categorization and unclassified elements may significantly influence the prediction or classification accuracies. To handle both issues, the normality test for categorizing data and rough sets approximation for improving the performance of the conventional regression models are considered. Some date sets are examined to evaluate the both idea. The result showed that number of category for each attribute depended on its normality testing. Additionally, the data reduction was able to improve the accuracy of rough-regression model significantly.
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Papers by Voni Apriana Dewi Dewi