Association rule is one of the data mining techniques to find associative combinations of items. There are several algorithms including Apriori, FP Growth, and CT-Pro. One of the advantages of the Apriori algorithm is that it produces many rules. To improve its result, one of the methods is by using the semantic web technology. This work proposes how the hierarchical type of ontology can be utilized by the Apriori algorithm to improve the results. The Apriori with ontology implements the Interestingness Rule (IR) which is a parameter to determine the degree of association between combinations of items in a dataset. The series of experiments show that the proposed idea can improve the results compare to the default Apriori algorithm. Keywords—Association Rule, Apriori, Ontology, Interestingness
{"title":"The Utilization of Ontology to Support The Results of Association Rule Apriori","authors":"D. Wardani, Achmad Khusyaini","doi":"10.11591/eecsi.v5.1642","DOIUrl":"https://doi.org/10.11591/eecsi.v5.1642","url":null,"abstract":"Association rule is one of the data mining techniques to find associative combinations of items. There are several algorithms including Apriori, FP Growth, and CT-Pro. One of the advantages of the Apriori algorithm is that it produces many rules. To improve its result, one of the methods is by using the semantic web technology. This work proposes how the hierarchical type of ontology can be utilized by the Apriori algorithm to improve the results. The Apriori with ontology implements the Interestingness Rule (IR) which is a parameter to determine the degree of association between combinations of items in a dataset. The series of experiments show that the proposed idea can improve the results compare to the default Apriori algorithm. Keywords—Association Rule, Apriori, Ontology, Interestingness","PeriodicalId":20498,"journal":{"name":"Proceeding of the Electrical Engineering Computer Science and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88959817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Assegaff, Akwan Sunoto, H. Hendrawan, Xaverius Sika Sika
The aimed of this study is to investigate the impact of social media utilization on the student's performances for knowledge sharing in teaching and learning progress. A research model on the basis of the Task-Technology Fit Theory and three hypotheses theory was developed for this study. Model and hypotheses then tested and validated using data obtained from a survey of respondents. The survey was conducted on students at a university in Indonesia. Of the 103 questionnaires filled out by members of the university, 75 questionnaires declared valid and used for further analysis. Data were analyzed using Partial Least Square (PLS) PLS Smart software utilizes V2. This study reveals that student performance in sharing knowledge with social media impact by technology characteristic and social media utilization.
{"title":"Social Media and User Performance in Knowledge Sharing","authors":"S. Assegaff, Akwan Sunoto, H. Hendrawan, Xaverius Sika Sika","doi":"10.11591/eecsi.v5.1611","DOIUrl":"https://doi.org/10.11591/eecsi.v5.1611","url":null,"abstract":"The aimed of this study is to investigate the impact of social media utilization on the student's performances for knowledge sharing in teaching and learning progress. A research model on the basis of the Task-Technology Fit Theory and three hypotheses theory was developed for this study. Model and hypotheses then tested and validated using data obtained from a survey of respondents. The survey was conducted on students at a university in Indonesia. Of the 103 questionnaires filled out by members of the university, 75 questionnaires declared valid and used for further analysis. Data were analyzed using Partial Least Square (PLS) PLS Smart software utilizes V2. This study reveals that student performance in sharing knowledge with social media impact by technology characteristic and social media utilization.","PeriodicalId":20498,"journal":{"name":"Proceeding of the Electrical Engineering Computer Science and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85359632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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