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Trust evaluation using data distribution technique on service computing
Biantoro Y.a, Suhardia, Bandung Y.a, Kurniawan N.B.b
a Institut Teknologi Bandung, School of Electrical Engineering and Informatics, Bandung, Indonesia
b Directorate of Statistical Information System Statistics of Indonesia, Jakarta, 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]© 2020 IEEE.In this modern era, the role of service computing has grown rapidly. Almost all service sectors are computationally based. The existence of service computing depends on the trust of its users. However, user ratings are spread across multiple systems and use different formats. The history recorded in the system is a record that can be used as an evaluation of the next service computing system development decision. In general, a trust record or a trust value is determined by a certain value. There are at least two categories, namely 0 and 1 (distrust and trust), or it could be more than two. Sometimes too many or too few categories are defined, making it difficult to conduct a trust evaluation analysis. This study aims to perform a redesign calculation to determine the category of trust. The calculation process is carried out using data distribution techniques using the available data sets. The result of this research is categorization evaluation of trust in service computing system. By obtaining a simpler category result, the old category can be adjusted to the new design, so that the results are not confusing when evaluating trustworthiness.[/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]Calculation process,Data distribution,Multiple systems,Service computing,Service sectors,Trust evaluation,Trust values,User rating[/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]Data distributions,Service computing,Trust evaluation[/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/ICITSI50517.2020.9264963[/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]