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Mobile-based SIWES Placement Recommendation System (A Case Study of Nigerian Universities)

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Orimoloye Segun Michael, Kolawole Blessing Oluwatosin

Orimoloye Segun Michael and Kolawole Blessing Oluwatosin. Mobile-based SIWES Placement Recommendation System (A Case Study of Nigerian Universities). International Journal of Computer Applications 152(9):1-6, October 2016. BibTeX

	author = {Orimoloye Segun Michael and Kolawole Blessing Oluwatosin},
	title = {Mobile-based SIWES Placement Recommendation System (A Case Study of Nigerian Universities)},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2016},
	volume = {152},
	number = {9},
	month = {Oct},
	year = {2016},
	issn = {0975-8887},
	pages = {1-6},
	numpages = {6},
	url = {},
	doi = {10.5120/ijca2016911103},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


The perennial problem students of higher institutions of learning in Nigeria face on an annual basis in finding suitable placements based on their locational and organizational preferences for the Mandatory Industrial training which varies from 6 months to a year cannot be overemphasized. They resort to manual means of seeking such placements themselves. Many end up frustrated and eventually settle for placements where they get minimal relevant training which in itself defeats the aim of the SIWES programme, established to help bridge the gap between the industry and the classroom. Unfortunately, no effort has been made prior to this work to come up with an automated system that assist in ameliorating this problem. The closest has been just to monitor the activities of the students after they must have commenced the programme. This work therefore proposes a Mobile based system that would be deployed and used on-the-go, automatically recommending suitable organizations based on the discipline and locational preferences of the prospective students. Data on suitable organizations on a locational basis was obtained from the SIWES unit of the research host institutions, based on previous Industrial trainings/internships was used to populate the database from which the mobile application does recommendations.


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Framework, Mobile, SIWES, Industrial Training, Placement, Recommendation