Combination of rough set and cosine similarity approaches in student graduation prediction.
Saved in:
| Title: | Combination of rough set and cosine similarity approaches in student graduation prediction. |
|---|---|
| Authors: | Go, Ratna Yulika1 ratna.yulika@esaunggul.ac.id, Asianto, Tinuk Andriyanti1 tinuk.andriyanti@esaunggul.ac.id, Setiowati, Dewi1 dewi.setiowati@esaunggul.ac.id, Meilisa, Ranny1 meilisa.rannya@gmail.com, Munthe, Christine Cecylia2 Chri010@brin.go.id, Kusumawardhana, R. Hendra3 r.hendra.k@gmail.com |
| Source: | International Journal of Electrical & Computer Engineering (2088-8708). Dec2025, Vol. 15 Issue 6, p6001-6011. 11p. |
| Subjects: | Rough sets, Case-based reasoning, Higher education, Academic achievement |
| Abstract: | Higher education institutions must deliver high-quality education that produces graduates who are knowledgeable, skilled, creative, and competitive. In this system, students are a vital asset, and their timely graduation rate is an important factor to consider. In the Department of Computer Science, a challenge arises in distinguishing between students who graduate on time and those who do not. With a low on-time graduation rate of just 1.90% out of 158 graduates, this issue could negatively affect the institution's accreditation evaluation. This research employs the case-based reasoning method, enhanced with an indexing process using rough sets and a prediction process utilizing cosine similarity. The testing, conducted using k-fold validation with 60%, 70%, and 80% of the data, produced average accuracy rates of 64.2%, 66.3%, and 65.6%, respectively. The test results indicate that the highest average accuracy of 66.3% was achieved with 70% of the cases. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Electrical & Computer Engineering (2088-8708) is the property of Institute of Advanced Engineering & Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 190950329 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Combination of rough set and cosine similarity approaches in student graduation prediction. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Go%2C+Ratna+Yulika%22">Go, Ratna Yulika</searchLink><relatesTo>1</relatesTo><i> ratna.yulika@esaunggul.ac.id</i><br /><searchLink fieldCode="AR" term="%22Asianto%2C+Tinuk+Andriyanti%22">Asianto, Tinuk Andriyanti</searchLink><relatesTo>1</relatesTo><i> tinuk.andriyanti@esaunggul.ac.id</i><br /><searchLink fieldCode="AR" term="%22Setiowati%2C+Dewi%22">Setiowati, Dewi</searchLink><relatesTo>1</relatesTo><i> dewi.setiowati@esaunggul.ac.id</i><br /><searchLink fieldCode="AR" term="%22Meilisa%2C+Ranny%22">Meilisa, Ranny</searchLink><relatesTo>1</relatesTo><i> meilisa.rannya@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Munthe%2C+Christine+Cecylia%22">Munthe, Christine Cecylia</searchLink><relatesTo>2</relatesTo><i> Chri010@brin.go.id</i><br /><searchLink fieldCode="AR" term="%22Kusumawardhana%2C+R%2E+Hendra%22">Kusumawardhana, R. Hendra</searchLink><relatesTo>3</relatesTo><i> r.hendra.k@gmail.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Electrical+%26+Computer+Engineering+%282088-8708%29%22">International Journal of Electrical & Computer Engineering (2088-8708)</searchLink>. Dec2025, Vol. 15 Issue 6, p6001-6011. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Rough+sets%22">Rough sets</searchLink><br /><searchLink fieldCode="DE" term="%22Case-based+reasoning%22">Case-based reasoning</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+education%22">Higher education</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+achievement%22">Academic achievement</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Higher education institutions must deliver high-quality education that produces graduates who are knowledgeable, skilled, creative, and competitive. In this system, students are a vital asset, and their timely graduation rate is an important factor to consider. In the Department of Computer Science, a challenge arises in distinguishing between students who graduate on time and those who do not. With a low on-time graduation rate of just 1.90% out of 158 graduates, this issue could negatively affect the institution's accreditation evaluation. This research employs the case-based reasoning method, enhanced with an indexing process using rough sets and a prediction process utilizing cosine similarity. The testing, conducted using k-fold validation with 60%, 70%, and 80% of the data, produced average accuracy rates of 64.2%, 66.3%, and 65.6%, respectively. The test results indicate that the highest average accuracy of 66.3% was achieved with 70% of the cases. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Electrical & Computer Engineering (2088-8708) is the property of Institute of Advanced Engineering & Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=190950329 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.11591/ijece.v15i6.pp6001-6011 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 6001 Subjects: – SubjectFull: Rough sets Type: general – SubjectFull: Case-based reasoning Type: general – SubjectFull: Higher education Type: general – SubjectFull: Academic achievement Type: general Titles: – TitleFull: Combination of rough set and cosine similarity approaches in student graduation prediction. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Go, Ratna Yulika – PersonEntity: Name: NameFull: Asianto, Tinuk Andriyanti – PersonEntity: Name: NameFull: Setiowati, Dewi – PersonEntity: Name: NameFull: Meilisa, Ranny – PersonEntity: Name: NameFull: Munthe, Christine Cecylia – PersonEntity: Name: NameFull: Kusumawardhana, R. Hendra IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20888708 Numbering: – Type: volume Value: 15 – Type: issue Value: 6 Titles: – TitleFull: International Journal of Electrical & Computer Engineering (2088-8708) Type: main |
| ResultId | 1 |
