DOI : https://doi.org/10.18517/ijaseit.10.2.8407

Decision Support System of Lecturer Selection Recommendation with Collaborative Filtering Method

Anton Setiawan Honggowibowo (1), Hero Wintolo (2), Yuliani Indrianingsih (3), Regina Maula Adiba (4)
(1) Department of Informatics, Adisutjipto College Of Technology, Janti Street, Blok-R, Lanud Adisutjipto Yogyakarta
(2) Department of Informatics, Adisutjipto College Of Technology, Janti Street, Blok-R, Lanud Adisutjipto Yogyakarta
(3) Department of Informatics, Adisutjipto College Of Technology, Janti Street, Blok-R, Lanud Adisutjipto Yogyakarta
(4) Department of Informatics, Adisutjipto College Of Technology, Janti Street, Blok-R, Lanud Adisutjipto Yogyakarta
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How to cite (IJASEIT) :
Honggowibowo, Anton Setiawan, et al. “Decision Support System of Lecturer Selection Recommendation With Collaborative Filtering Method”. International Journal on Advanced Science, Engineering and Information Technology, vol. 10, no. 2, Apr. 2020, pp. 485-90, doi:10.18517/ijaseit.10.2.8407.
Citation Format :
The use of decision support systems for the selection of the best lecturers at Adisutjipto Institute of Technology (STTA) is not yet at the level of application. The average tertiary institution in selecting the best lecturers uses certain criteria, for example the criteria in teaching, research and community service. Of the three indicators of lecturer performance in Indonesia, we only use two indicators, namely research and community service. From these two indicators, we made five criteria, namely the number of presenters at the conference, the amount of community service, the number of unpublished research, the number of published research, and the number of citations of scientific articles. The selection was made by users, namely STTA Director, Vice Director for Academic Affairs, Vice Director for Financial Affairs and Community Service Research Center to 62 lecturers who were active in research, community service and publications indexed on Google Scholar. This user restriction is adjusted to the organizational structure at our university, where the five users have authority in assessing the performance of lecturers and giving awards to lecturers who are declared as the best lecturers. After Collaborative Filtering method is done to predict the final result using the rating given by the user. Based on the results of the system testing, it was concluded that the system that was built could be a solution to help select lecturers who were eligible to be given awards as the best of lecturer in the field of research and community service.

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