Classification of Trends in Lecturer Research Fields Using Naive Bayes Method

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Sulthan Rafif, Pramana Yoga Saputra, Moch Zawaruddin Abdullah

2021 Proceedings - IEIT 2021: 1st International Conference on Electrical and Information Technology Conference paper Cited by 1 Quartile

Abstract

Lecturers must contribute to publishing scientific papers following their respective research groups. Sometimes, the publications conducted by lecturers consist of various fields of research. So that lecturers need to determine their research interest in the research being carried out. The large number of lecturers' publications consisting of various research fields makes it difficult for lecturers to determine research interests. Based on these problems, this study tries to create a system that can determine the propensity of lecturers towards certain fields of research. The classification system applies the Naive Bayes method. The results of the classification are used to determine the tendency of each JTI POLINEMA lecturer towards a particular field of research. The results of the performance of the Naive Bayes classification model for the classification of research fields in the publication title show an accuracy of 57%, precision of 57%, recall of 57%, and an error value of 43%. © 2021 IEEE.

Affiliations

State Polytechnic of Malang, Information Technology Department, Malang, Indonesia

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