A semi-supervised learning approach for predicting student's performance: First-year students case study

Yekti Widyaningsih; Nur Fitriani; Devvi Sarwinda

doi:10.1109/ICTS.2019.8850950

A semi-supervised learning approach for predicting student's performance: First-year students case study

Yekti Widyaningsih, Nur Fitriani, Devvi Sarwinda

Department of Mathematics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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 Naïve 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.

Original language	English
Title of host publication	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
Number of pages	5
ISBN (Electronic)	9781728121338
DOIs	https://doi.org/10.1109/ICTS.2019.8850950
Publication status	Published - 1 Jul 2019
Event	12th International Conference on Information and Communication Technology and Systems, ICTS 2019 - Surabaya, Indonesia Duration: 18 Jul 2019 → …

Publication series

Name	Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019

Conference

Conference	12th International Conference on Information and Communication Technology and Systems, ICTS 2019
Country/Territory	Indonesia
City	Surabaya
Period	18/07/19 → …

Keywords

K-Means Clustering
Naïve Bayes Classifier
Semi-supervised Learning
Student Performance

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10.1109/ICTS.2019.8850950

Cite this

Widyaningsih, Y., Fitriani, N., & Sarwinda, D. (2019). A semi-supervised learning approach for predicting student's performance: First-year students case study. In Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019 (pp. 291-295). [8850950] (Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICTS.2019.8850950

Widyaningsih, Yekti ; Fitriani, Nur ; Sarwinda, Devvi. / A semi-supervised learning approach for predicting student's performance : First-year students case study. Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 291-295 (Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019).

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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.",

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Widyaningsih, Y, Fitriani, N & Sarwinda, D 2019, A semi-supervised learning approach for predicting student's performance: First-year students case study. in Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019., 8850950, Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019, Institute of Electrical and Electronics Engineers Inc., pp. 291-295, 12th International Conference on Information and Communication Technology and Systems, ICTS 2019, Surabaya, Indonesia, 18/07/19. https://doi.org/10.1109/ICTS.2019.8850950

A semi-supervised learning approach for predicting student's performance : First-year students case study. / Widyaningsih, Yekti; Fitriani, Nur; Sarwinda, Devvi.

Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 291-295 8850950 (Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Widyaningsih Y, Fitriani N, Sarwinda D. A semi-supervised learning approach for predicting student's performance: First-year students case study. In Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 291-295. 8850950. (Proceedings of 2019 International Conference on Information and Communication Technology and Systems, ICTS 2019). https://doi.org/10.1109/ICTS.2019.8850950

A semi-supervised learning approach for predicting student's performance: First-year students case study

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