Year: 2016
Type: article
Abstract: The Student's competence determination is a very important thing because it will ease the students in entering the work world which is appropriate with their competence in which competence has positive effect to someone's performance on his work.Data clustering technique has been used widely nowadays.However on the real world, the problems about the features used in data clustering process is still very much neglected, thus there are often features used are not quite relevant in the data clustering process.Therefore this research uses the combination between Genetic Algorithm and Fuzzy C-Means in the student's competence determination.The data used is the data of STIKOM Bali students in Information System programme.The genetic algorithm is used to determine the relevant features and Fuzzy C-Means is used in data clustering optimally.The combination between these two algorithms result in 77 features had by the dataset, but only 61 features are relevant and valid to use in clustering process.From the experiment result, the combination of Genetic Algorithm and Fuzzy C-Means gives better result than using only Fuzzy C-Means with the average percentage on the test conducted is 88.89%.
Source: Majalah Ilmiah Teknologi Elektro
Authors: Electrical Engineering Universitas Udayana, Rosalia Hadi, I Ketut Gede Darma Putra, I Nyoman Satya Kumara
Institution: Udayana University
Language: Indonesian
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $15
OpenAlex ID: W2554887611