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Erschienen in:
2017 | OriginalPaper | Buchkapitel
A Data Mining Approach to Improve Remittance by Job Placement in Overseas
verfasst von : Ahsan Habib Himel, Tonmoy Sikder, Sheikh Faisal Basher, Ruhul Mashbu, Nusrat Jahan Tamanna, Mahmudul Abedin, Rashedur M. Rahman
Erschienen in: Computational Collective Intelligence
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Abstract
Remittance or foreign currency transaction plays an important role in increasing a country’s financial growth. Bangladesh is a country with a reputation in manpower export and every year it receives a considerable amount of remittance. Yet the remittance can be improved further by providing the workers with the information of their future earnings.
We propose a solution that will help the workers as well as the government to decide which country/countries will be best for workers in terms of earning, thus increasing the country’s annual remittance. The research outcome from this paper could help the government to export the manpower to the right country and the workers who are planning to move abroad with a vision to work for the best suitable job with respect to their skill. Besides, the findings could help in reducing the unexpected returns of the workers and stop the bad experience the workers endure abroad.