Comparation of Support Vector Machine and Artificial Neural Network Algorithm for Lecturer Performance Classification
Year: 2021
Type: article
Abstract: The purpose of this study is to classify the performance of lecturers from a dataset taken from the bkd.ubharajaya.ac.id application.Many universities have not been effective in assessing the performance of lecturers so that the data that has been obtained from each lecturer's report only becomes stored data, not yet into knowledge that will be used as decision makers.The research method used in this research is to start by acquiring data from the bkd.ubharajaya.ac.id application which will then be analysed through data mining stages by pre-processing data that is feasible to create a dataset.The dataset that has been created is then analysed using the 10-fold cross validation method which will divide the data into training data and testing data which will then be made a classification model using the Support Vector Machine (SVM) and Artificial Neural Network (ANN) algorithms.The expected research results with this application can classify the performance of lecturers who have the best accuracy to be used as a decision-making system.
Source: IJARCCE
Authors: Wowon Priatna, Rakhmat Purnomo
Institution: Universitas Bhayangkara Jakarta Raya
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W3203652796