Assessing Academic Information System Performance Through Sentiment Analysis
| Dublin Core | PKP Metadata Items | Metadata for this Document | |
| 1. | Title | Title of document | Assessing Academic Information System Performance Through Sentiment Analysis |
| 2. | Creator | Author's name, affiliation, country | Zafira Thuraya; Universitas Sriwijaya; Indonesia |
| 2. | Creator | Author's name, affiliation, country | Ali Ibrahim; Universitas Sriwijaya; Indonesia |
| 2. | Creator | Author's name, affiliation, country | Yadi Utama; Universitas Sriwijaya; Indonesia |
| 2. | Creator | Author's name, affiliation, country | Dwi Rosa Indah; Universitas Sriwijaya; Indonesia |
| 3. | Subject | Discipline(s) | Information System, Master of Computer Science |
| 3. | Subject | Keyword(s) | Information System; Sentiment analysis; Naïve Bayes; Social Media; Twitter |
| 4. | Description | Abstract | The Academic Information System (SIMAK) at Sriwijaya University plays a crucial role in facilitating student academic activities; however, it faces several technical issues that affect user satisfaction, including server outages and challenges in data access. This dissatisfaction serves as a vital metric for evaluating the system's effectiveness. This study aims to analyze student sentiment regarding SIMAK utilizing the Naïve Bayes method. A total of 92 tweets were gathered from Twitter through web scraping, which were then categorized into manually labeled training and test datasets for model validation. The data underwent processing that included text cleaning and the application of Term Frequency-Inverse Document Frequency (TF-IDF) to assess the significance of words within a collection of documents. The evaluation results indicated that the model achieved an accuracy of 65%, with a precision of 63% for negative sentiment and a recall of 100%. In contrast, positive sentiment exhibited a low precision of 12.5% and an F1-score of 22.2%, highlighting difficulties in identifying positive sentiment due to data imbalance. The model demonstrated greater effectiveness in identifying user grievances, particularly concerning server disruptions, data delays, and challenges in completing Study Plan Cards and accessing grades. These findings provide valuable insights for SIMAK maintainers to enhance system reliability and user experience. Future research should aim to broaden data coverage and explore alternative analytical methods to yield more representative outcomes. |
| 5. | Publisher | Organizing agency, location | Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer |
| 6. | Contributor | Sponsor(s) | |
| 7. | Date | (YYYY-MM-DD) | 2025-05-13 |
| 8. | Type | Status & genre | Peer-reviewed Article |
| 8. | Type | Type | |
| 9. | Format | File format | |
| 10. | Identifier | Uniform Resource Identifier | https://sistemasi.ftik.unisi.ac.id/index.php/stmsi/article/view/5130 |
| 10. | Identifier | Digital Object Identifier (DOI) | https://doi.org/10.32520/stmsi.v14i3.5130 |
| 11. | Source | Title; vol., no. (year) | Sistemasi: Jurnal Sistem Informasi; Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi |
| 12. | Language | English=en | en |
| 13. | Relation | Supp. Files |
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| 14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
| 15. | Rights | Copyright and permissions |
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