|
Vol.13, No.3, August 2024. ISSN: 2217-8309 eISSN: 2217-8333
TEM Journal
TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS Association for Information Communication Technology Education and Science |
Analysis of Instruments for Implementing Intelligent Job Matching Models
Geovanne Farell, Rido Wahyudi, Igor Novid, Delsina Faiza, Sartika Anori
© 2024 Geovanne Farell, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Citation Information: TEM Journal. Volume 13, Issue 3, Pages 2186-2194, ISSN 2217-8309, DOI: 10.18421/TEM133-46, August 2024.
Received: 24 March 2024. Revised: 11 July 2024.
Abstract:
Vocational high schools in Indonesia face challenges in producing graduates who meet the needs of the job market. The link and match policy along with the Job Matching system are proposed to enhance curriculum relevance to the workforce. The intelligent job matching model, which integrates machine learning technology, is expected to provide job recommendations aligned with graduates' competencies. Data analysis techniques used include qualitative and quantitative statistical analysis, encompassing Validity Analysis, Practicality Analysis, and Effectiveness Analysis. The intelligent job matching model has proven effective in assisting in matching vocational high school students' competencies with workforce demands in the industry. In the 2023 job fair, the success ratio of students invited for interviews until the employment process reached 53.13%, exceeding the Ministry of education and culture's target of 40%. This indicates that the model can provide job recommendations accurately enough, aiding in improving the direct employment rate of vocational high school students. Research indicates that the intelligent job matching model is effective in facilitating students' transition to the workforce. The model has been tested for validity, practicality, and effectiveness in enhancing students' employability and strengthening the relationship between education and industry.
Keywords – Machine learning, content based filtering, intelligent job matching, vocational high school. |
|
----------------------------------------------------------------------------------------------------------- ----------------------------------------------------------------------------------------------------------- |