Enter your keyword

2-s2.0-85065183715

[vc_empty_space][vc_empty_space]

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

Haryono F.D.a, Kistijantoro A.I.a

a School of Electrical Engineering and Informatics, Badung Institute of Technology, Bandung, Indonesia

[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2018 IEEE.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.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Arithmetic expression,Boolean expression indexing,Boolean expressions,Grid-based clustering,Processing activity,Space clustering,State of the art,Survey data[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Be-tree,Boolean expression indexing,Data structure algorithm,Optimization,Survey data validation[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICITSI.2018.8696000[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]