Analysis and Development of Boolean Expression Matching on Survey Data Validation : (Case Study: Survey and Census of Statistics Indonesia)

Optimizing survey data validation is a challenge in survey data processing. Validating survey data is one of the survey data processing activities that need many resources and spend much time to process because of a large amount of data and rule. Survey data validation is about processing rule that can be formed in the boolean expression. Be-tree is state of the art of boolean expression indexing for discrete data. Survey data validation contains continues data type, arithmetic expression, and null data type expression that not handled by be-tree. We proposed method indexing boolean expression that contains continues data type, arithmetic expression and null data type expression based on be-tree. Our experiment shows that be-tree can be used in survey data validation with all form of validation rules. Be-tree was proven more efficient than traditional survey data validation methods. We also used a balanced interval tree with red black implementation for clustering space in be-tree and was shown a little more efficient than grid-based clustering, an original space clustering in be-tree.