Browsing by Author "Akintola, A. G."

Now showing 1 - 3 of 3
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    Borrowing patterns monitoring in Library: Application of Apriori algorithm
    (International Journal of Information Processing and Communication, 2015) Adewole, K. S.; Akintola, A. G.; Mabayoje, M. A.; Ogbomon, G. A.
    Data is a valuable tool for any institution, and with the world advancing in technology, data stored in database management systems are growing in different capacities in almost all organization. The opportunities of database management systems have been explored. However, many organizations have not been able to leverage these opportunities in gaining business intelligence from their repositories. This paper addresses the issue of knowledge discovery from large databases using association rule mining. Apriori algorithm is implemented to discover hidden knowledge from a library database. Data depicting nine (9) different books were used within forty-seven (47) unique transactions. Eighteen (18) unique transactions were generated from the database showing the borrowing pattern of library users. The frequencies of borrowing of books were obtained as well as the associations. The result shows that borrowing a particular book may leads to borrowing another book as revealed in the association between Data structure in C (DS) textbook and Programming in C (C) textbook. The discovered pattern can help librarians in restructuring their bookshelf arrangement, and for book recommendation system. This system can also help students to have good knowledge different related books.
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    Frequent Pattern and Association Rule Mining from Inventory Database using Apriori Algorithm
    (African Journal of Computing & ICT, 2014) Adewole, K. S.; Akintola, A. G.; Abdulsalam, S. O.; Ajiboye, A. R.
    Recently, data mining has attracted a great deal of attention in the information industry and in a Society where data continue to grow on a daily basis. The availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge is the major focus of data mining. The information and knowledge obtained from large data can be used for applications ranging from market analysis, fraud detection, production control, customer retention, and science exploration. A record in such data typically consists of the transaction date and the items bought in the transaction. Successful organizations view such databases as important pieces of the marketing infrastructure. This paper considers the problem of mining association rules between items in a large database of sales transactions in order to understand customer-buying habits for the purpose of improving sales. Apriori algorithm was used for generating strong rules from inventory database. It was found that for a transactional database where many transaction items are repeated many times as a superset in that type of database, Apriori is suited for mining frequent itemsets. The algorithm was implemented using PHP, and MySQL database management system was used for storing the inventory data. The algorithm produces frequent itemsets completely and generates the accurate strong rules.
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    Student Web Self-Service Portal for a Tertiary Institution
    (Covenant Journal of Informatics & Communication Technology (CJICT), 2016) Akintola, A. G.; Adewole, K. S.; Mabayoje, M. A.; Oke, J. O.
    The optimum condition for students to study is in an environment where they can access virtually all they need to know about courses, lecturers, locate places (for fresh and prospective students), validate staff identity, access past examination questions easily, identify vacant student hostels within and outside the school premises. Some of the reasons for students’ failure can be attributed to finding accommodation within or outside the school premises. Also, fresh students find it difficult to locate specific places in the university environment and some students find it very difficult to interact with staff. This paper presents a student self-service portal to address some of these challenges. Unified Modeling Language (UML) was used to model the system. The model was implemented using Microsoft C#, Microsoft ASP.net, Microsoft SQL Server, and Google Map. The proposed system was tested and the result obtained during the execution shows that the system is capable of addressing some of the challenges confronted by students.