Synchronisation Model of Campus-Industry Partnership Through Smart Expert System Hybrid Advisory for Industrial Internship Students and Teaching Assistance in the Era of Independent Learning

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Abstract

The objectives of this research include (1) developing smart expert system innovation integrated hybrid advisory; and (2) Testing the attractiveness and feasibility of the hybrid advisory integrated smart expert system innovation prototype. The method in this research is in the form of research and development (Re-search and Development). Where the method includes a preliminary study; model design; development of model prototypes; model prototype testing; model prototype revision; validated model prototype results; model prototype experimentation; tested models; and dissemination. all state universities in East Java (students, equipped with lecturers, officials in PT and stakeholders). The research instrument used questionnaires, documents, structured surveys, observations, and in-depth interviews. The results of this study include: (1) the innovations developed have synchronous and asynchronous online guidance features, submit reports and daily assignments, student progress reports, live chat with supervisors and instructors, daily attendance, to review report results; and (2) the Smart Expert System Integrated Hybrid Advisory innovation developed has valid results without revision with an average score of 90.1 (user benefit aspect), an average score of 90.5 (application display aspect), an average score of 93,8 (newness of information aspect), average score of 97.6 (content aspect), average score of 90.6 (user-friendliness aspect), average score of 93.8 (competency achievement aspect).

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APA

Putra, A. B. N. R., Sumarli, Suhartadi, S., Kiong, T. T., & Rahmawati, A. D. (2023). Synchronisation Model of Campus-Industry Partnership Through Smart Expert System Hybrid Advisory for Industrial Internship Students and Teaching Assistance in the Era of Independent Learning. Journal of Technical Education and Training, 15(3 Special Issue), 142–153. https://doi.org/10.30880/jtet.2023.15.03.013

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