Browsing by Author "Oyediran, M.O."
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Item Development of Efficient E-Recruitment System for University Staff in Nigeria(Circulation in Computer Science, 2016-05-05) Amusan, D. G.; Oyediran, M.O.The development of e-recruitment system is web-based tool used in order to reduce communication gap between job seekers and employers. E-recruitment, also known as online recruitment, is the practice of using technology and in particular Web-based resources for tasks involved with finding, attracting, assessing, interviewing and hiring new personnel. Most of the existing mode of recruitment (manual recruitment) takes much time in processing the application form, existing system will not automatically send feedback to all applicant whose meet up with the job requirement but with the help of the developed system there is reduction in time to process the application form and there is automatic feedback from the employer to the job seeker that meet up with requirement. The objective of this work is to developed an efficient e-recruitment system capable of managing all stages of the e- recruitment process, including multi-job posting, agency channel management and candidate filtering to identify the most relevant candidates...Item Hybrid Design using Counter Propagation Neural Network-Genetic Algorithm Model for the Anomaly Detection in Online Transaction(International Journal of Advances in Scientific Research and Engineering (ijasre), 2019-09-20) Amusan, D.G.; Olabode, A.O.; Ojo, O.S.; Folowosele, A.O.; Oyediran, M.O.In e-commerce, credit card fraud is an evolving challenge. The increase in the number of credit card transactions provides more opportunity for fraudsters to steal credit card numbers and execute fraud. Fraud detection is a continuously evolving discipline to tackle ever changing tactics to commit fraud. Existing fraud detection systems have not been so much efficient to reduce fraud transaction rate. Improvement in fraud detection practices has become essential to maintain existence of payment system. This research designed hybrid of Counter Propagation Neural Network and genetic algorithm (CPNN-GA) for the detection of anomaly in any online transactions.