@inproceedings{518a33d186344c378f666371b47fe156,
title = "A semi-supervised learning approach for predicting student's performance: First-year students case study",
abstract = "Students performance is an essential part of a higher learning institution because one of the criteria for a high -quality university is based on its excellent record of academic achievements. The first-year of the lecture is the student period of laying the foundation that will affect academic success because first-year plays an important role in shaping the attitudes and performance of students in the following years. In this study, a semi-supervised learning approach is used to classify the performance of first-year students in the Department of Mathematics, Universitas Indonesia. Student performance will be divided into two categories, namely medium and high. The sample in this study consist of 140 first-year students with 27 features. There are two processes used i.e. clustering and the classification process. In the clustering process, the data is divided into three clusters using K-Means Clustering and the Na{\"i}ve Bayes Classifier is chosen to classify it. The performance of the proposed algorithms is stated by accuracy, sensitivity, and specificity value i.e. 96%, 92.86%, and 100% respectively.",
keywords = "K-Means Clustering, Na{\"i}ve Bayes Classifier, Semi-supervised Learning, Student Performance",
author = "Yekti Widyaningsih and Nur Fitriani and Devvi Sarwinda",
year = "2019",
month = jul,
day = "1",
doi = "10.1109/ICTS.2019.8850950",
language = "English",
series = "Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "291--295",
booktitle = "Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019",
address = "United States",
note = "12th International Conference on Information and Communication Technology and Systems, ICTS 2019 ; Conference date: 18-07-2019",
}