Search Results - (( exploring practices mining algorithm ) OR ( java implication based algorithm ))

A systematic literature review on the impact of data mining on workforce privacy and employment practices: ethical concerns and risks by Ismail, Azratul Ain Nadiah, Mohamad, Ahmad Nadzri

“…Data mining tools enabled by artificial intelligence can change the norms in employment practices. …”
Get full text
Get full text
Get full text

Modeling and simulation of the industrial numerical distance relay aimed at knowledge discovery in resident event reporting by Othman, Mohammad Lutfi, Aris, Ishak, Abdul Wahab, Noor Izzri

“…This is justified by the practicality and necessity of divulging the decision algorithm hidden in the recorded relay event report using computational intelligence-based data mining. …”
Get full text
Get full text

Analysis of Traffic Accident Patterns Using Association Rule Mining by Yudy, Pranata, Tri Basuki, Kurniawan, Edi Surya, Negara, Ahmad Haidar, Mirza

“…This study also demonstrated the practicality of the apriori algorithm in analyzing extensive datasets to extract actionable insights. …”
Get full text
Get full text
Get full text
Get full text

Forecast of Muslimah fashion trends in Caca's company / Muhammad Saifullah Mohd Taip by Mohd Taip, Muhammad Saifullah

“…This predictive analysis is carried out to learn future predictions about the classification of each outfit, its colour, and its size, and the project begins with the study's first data collection and exploration before putting data mining activities into practise. …”
Get full text
Get full text

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

Get full text
Get full text
Get full text

Irrelevant feature and rule removal for structural associative classification by Mohd Shaharanee, Izwan Nizal, Jamil, Jastini

“…In the classification task, the presence of irrelevant features can significantly degrade the performance of classification algorithms,in terms of additional processing time, more complex models and the likelihood that the models have poor generalization power due to the over fitting problem.Practical applications of association rule mining often suffer from overwhelming number of rules that are generated, many of which are not interesting or not useful for the application in question.Removing rules comprised of irrelevant features can significantly improve the overall performance.In this paper, we explore and compare the use of a feature selection measure to filter out unnecessary and irrelevant features/attributes prior to association rules generation.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data items.Empirical results confirm that by utilizing feature subset selection prior to association rule generation, a large number of rules with irrelevant features can be eliminated.More importantly, the results reveal that removing rules that hold irrelevant features improve the accuracy rate and capability to retain the rule coverage rate of structural associative association.…”
Get full text
Get full text
Get full text

Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush