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All Journal International Journal of Research and Applied Technology (INJURATECH)
Saputra, C R
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Implementing Recommendation Application Service Information Systems for Candidate Workers Needs in the Covid-19 Pandemic Suwita, Ferry Stephanus; Saputra, C R; Feno, D; Novaldo, A
International Journal of Research and Applied Technology (INJURATECH) Vol. 4 No. 1 (2024): International Journal of Research and Applied Technology (INJURATECH)
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injuratech.v4i1.13914

Abstract

Every fresh graduate will need and find a job. However, it isn't easy to get a job, especially when workers are mostly done online. Thus, prospective workers need a variety of tools to assist them in their work, such as applications used for works. Therefore, this case aims to create a web-based information system to help their work. It is expected to improve the soft skills and productivity of workers. The results of the application recommendation information are obtained from the survey form in which all questions are related to the needs of the website users of the application. The information is then directly processed by the web system, and the output will get application recommendations along with usage information, info features, and platforms that can be used. The method used in this study includes the analysis phase starting from gathering information and making ideas, followed by making preliminary designs to making prototypes, testing, and evaluating implementation. Based on the testing results, the recommendation can help prospective workers increase knowledge about the right application to be used on the work to be done and prevent the use of less efficiency. This research concludes that with the help of recommendation, application services can help prevent workers from using applications that are less efficient for their work and increase soft skills and productivity.
Co-Authors Feno, D Novaldo, A Suwita, Ferry Stephanus