IMPLEMENTATION OF DATA MINING ROUGHT SET IN ANALYZING LECTURER PERFORMANCE
DOI:
https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v7i2.4842Abstract
Lecturers are professional educators or scientists with the main task of transforming, developing, and disseminating science, technology, and art through education, research, and community service by the Tridharma of Higher Education. The main task of lecturers is to implement the tri dharma of higher education with the scope of activities in the form of teaching, research, and community service. Based on this, the Payakumbuh College of Technology assesses lecturers' performance to maintain the educational institution's quality. A method is needed to identify the quality of lecturers' performance. Lecturer performance can be determined using a rough set approach with several stages. Rough set is a data mining technique applied in several fields, including selecting study programs and predicting mobile phone sales income. Based on the results of using the rough set method, lecturer performance information is produced in a certain period, which aims to help leaders understand the possible performance of lecturers in a certain period. The benefit that can be obtained is that the knowledge obtained through the rough set method can determine the possibility of achieving lecturer performance.
References
Z. Yusuf, Sarboini and R. Ardiana. "The Influence of Human Resource Development on Lecturer Performance in Improving the Vision and Mission of the Faculty of Economics, Serambi Mecca University." JEMSI (Journal of Economics, Management and Accounting), Vol. 7, no. 2, pp: 60-73, 2021.
Ahyuna et al. "Analysis of the Application of the MABAC Method with Entropy Weighting in Lecturer Performance Assessment in the Era of Society 5.0". Building of Informatics, Technology and Science (BITS) Volume 5, No 1, pp: 29−39, 2023.
D. Hartama and Hartono. "Performance Analysis of STMIK IBBI Lecturers Using the Rough Set Method." National Seminar on Information Technology and Multimedia, 2016.
D. Hartini, "Implementation of Data Mining Rough Set in Analyzing Lecturer Performance," on Binary Scientific Journal STMIK Bina Nusantara Jaya, vol. 1, no. 02, pp. 36-42, 2019.
S. Utari. "Application of the Rought Set Algorithm to Predict the Number of Product Demands." Bulletin of Data Science, Vol 1, No 2, pp 73-79, 2022.
B. Davvaz, I. Mukhlash, and Soleha. “Fuzzy Sets and Rough Sets”. Limits: Journal of Mathematics and Its Applications, Vol. 18, no. 1, pp: 79-94, 2021.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Tegas Hadiyanto, Fitri Permata Sari, Lela Budiarti, Afriadi Syahputra, Isna Wirahmadayanti
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish their manuscripts through the Journal of Information Systems and Computer Science agree to the following:
- Copyright to the manuscripts of scientific papers in this Journal is held by the author.
- The author surrenders the rights when first publishing the manuscript of his scientific work and simultaneously the author grants permission / license by referring to the Creative Commons Attribution-ShareAlike 4.0 International License to other parties to distribute his scientific work while still giving credit to the author and the Journal of Information Systems and Computer Science as the first publication medium for the work.
- Matters relating to the non-exclusivity of the distribution of the Journal that publishes the author's scientific work can be agreed separately (for example: requests to place the work in the library of an institution or publish it as a book) with the author as one of the parties to the agreement and with credit to sJournal of Information Systems and Computer Science as the first publication medium for the work in question.
- Authors can and are expected to publish their work online (e.g. in a Repository or on their Organization's/Institution's website) before and during the manuscript submission process, as such efforts can increase citation exchange earlier and with a wider scope.