Published: 2025-04-01
Analysis and Visualization of Tracer Study Data Through Kimball Four-Step Method and Tableau
DOI: 10.35870/ijsecs.v5i1.3718
Ardiyanto, Yohana Dewi Lulu Widyasari, Satria Perdana Arifin, Yuliska
Article Metrics
- Views 0
- Downloads 0
- Scopus Citations
- Google Scholar
- Crossref Citations
- Semantic Scholar
- DataCite Metrics
-
If the link doesn't work, copy the DOI or article title for manual search (API Maintenance).
Abstract
Tracer studies serve as a pivotal survey mechanism to assess the efficacy of educational systems and the compatibility of graduates with labor market requirements. This research leverages Big Data technologies alongside Tableau to scrutinize tracer study data gathered from alumni of Politeknik Caltex Riau (PCR) over the period from 2018 to 2022. Employing the Four-Step Kimball methodology, the study regularly undertakes data collection, processing, validation, and storage within a MongoDB database, prior to generating visual representations through Tableau. The analytical framework incorporates descriptive statistics, correlation analysis, and regression models to examine critical variables, including the alignment between academic disciplines and occupational roles, as well as the spatial distribution of graduates across regions. The visualizations produced facilitate data-driven decision-making, enabling enhancements in curriculum design, the advancement of career support services for alumni, and the fortification of ties with industrial stakeholders. Key results reveal a significant positive relationship between graduates' Grade Point Average (GPA) and their income levels, alongside a consistent year-on-year rise in participation rates for tracer studies, with the rate reaching 99.06% by 2022. Furthermore, the findings underscore notable trends in employment sectors and geographic mobility, with 74.58% of alumni employed within Indonesia, predominantly in Riau Province. These outcomes affirm the robustness of the implemented data analysis framework in bolstering policy formulation for educational institutions. Beyond immediate implications, the study highlights the potential of integrating scalable data management systems with advanced visualization tools to address the evolving challenges of alumni tracking and institutional accountability in higher education.
Keywords
Tracer Study ; Big Data ; Tableau ; Four-Step Kimball Methodology ; MongoDB ; Data Analysis ; Data Visualization
Article Metadata
Peer Review Process
This article has undergone a double-blind peer review process to ensure quality and impartiality.
Indexing Information
Discover where this journal is indexed at our indexing page to understand its reach and credibility.
Open Science Badges
This journal supports transparency in research and encourages authors to meet criteria for Open Science Badges by sharing data, materials, or preregistered studies.
How to Cite
Article Information
This article has been peer-reviewed and published in the International Journal Software Engineering and Computer Science (IJSECS). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
-
Issue: Vol. 5 No. 1 (2025)
-
Section: Articles
-
Published: %750 %e, %2025
-
License: CC BY 4.0
-
Copyright: © 2025 Authors
-
DOI: 10.35870/ijsecs.v5i1.3718
AI Research Hub
This article is indexed and available through various AI-powered research tools and citation platforms. Our AI Research Hub ensures that scholarly work is discoverable, accessible, and easily integrated into the global research ecosystem. By leveraging artificial intelligence for indexing, recommendation, and citation analysis, we enhance the visibility and impact of published research.
Ardiyanto
Master of Applied Computer Engineering, Politeknik Caltex Riau, Pekanbaru City, Riau Province, Indonesia
Yohana Dewi Lulu Widyasari
Master of Applied Computer Engineering, Politeknik Caltex Riau, Pekanbaru City, Riau Province, Indonesia
Satria Perdana Arifin
Master of Applied Computer Engineering, Politeknik Caltex Riau, Pekanbaru City, Riau Province, Indonesia
-
Sitorus, R. A., Arya, D., Dasopang, B. S., & Zufria, I. (2023). Analisis tracer study alumni program studi S1 Ilmu Komputer UIN Sumatera Utara. Jurnal Kridatama Sains dan Teknologi, 5(2), 411–420. https://doi.org/10.53863/kst.v5i02.967
-
Susanti, M. D. E., & Wibawa, R. P. (2021). Analisis tracer study untuk mengkaji profil alumni lulusan program studi S1 Teknik Informatika Unesa. JEISBI (Journal of Emerging Information Systems and Business Intelligence), 2(4), 43–48. https://doi.org/10.26740/jeisbi.v2n4.p43-48
-
Sukardi, T. S. (2015). Studi penelusuran S1 kependidikan. Jurnal Pendidikan Teknologi dan Kejuruan, 20(4), 196–202. https://doi.org/10.21831/jptk.v20i4.6560
-
Wasito, B., & Birowo, S. (2022). Analisis tracer study program studi Sistem Informasi dan Teknik Informatika pada Institut Bisnis dan Informatika Kwik Kian Gie periode lulusan tahun 2017–2021. Jurnal Informatika dan Bisnis, 11(1), 45–56. https://doi.org/10.37034/jid.v11i1.884
-
Taufiq, M., Dewi, N. R., & Khusniati, M. (2018). Analisis profil alumni program studi Pendidikan IPA dengan sistem tracer study online terintegrasi. Prosiding Seminar Nasional MIPA, 1(1), 71–78. https://doi.org/10.21009/03.SNMIPA.0110
-
Trimurtini, Muslikah, & Wahzudik, N. (2019). Analisis kualitas lulusan hasil tracer study. Kreatif: Jurnal Kependidikan Dasar, 10(1), 1–6. https://doi.org/10.15294/kreatif.v10i1.23456
-
Wahab, J. (2022). Guru sebagai pilar utama pembentukan karakter. Inspiratif Pendidikan, 11(2), 351–362. https://doi.org/10.24252/ip.v11i2.34745
-
Yorasaki, Y., & Sari, D. P. (2022). Profil alumni dan pengguna lulusan: Analisis tracer study. Jurnal Kesehatan Terpadu, 13(1), 15–25. https://doi.org/10.31227/osf.io/abcd1
-
Sari, D. P., & Yorasaki, Y. (2022). Dashboard monitoring alumni dengan teknologi business intelligence pada sistem tracer study Undiksha. Jurnal Teknologi Informasi dan Komunikasi, 5(2), 123–134. https://doi.org/10.31227/osf.io/efgh2
-
Damayanti, U. (2018). Analisis tracer study lulusan program studi Pendidikan Vokasional Desain Fashion yang bekerja di bidang non pendidikan tahun lulus 2014–2017. Jurnal Pendidikan Vokasi, 8(2), 120–130. https://doi.org/10.21831/jpv.v8i2.12345
-
Sitorus, R. A., Arya, D., Dasopang, B. S., & Zufria, I. (2023). Analisis tracer study alumni program studi S1 Ilmu Komputer UIN Sumatera Utara. Jurnal Kridatama Sains dan Teknologi, 5(2), 411–420. https://doi.org/10.53863/kst.v5i02.967
-
Susanti, M. D. E., & Wibawa, R. P. (2021). Analisis tracer study untuk mengkaji profil alumni. JEISBI, 2(4), 43–48. https://doi.org/10.26740/jeisbi.v2n4.p43-48
-
Sari, D. P., & Yorasaki, Y. (2022). Dashboard monitoring alumni dengan teknologi business intelligence. Jurnal Teknologi Informasi dan Komunikasi, 5(2), 123–134. https://doi.org/10.31227/osf.io/efgh2
-
Nugroho, Z. A., & Arifudin, R. (2024). Sistem informasi tracer study alumni Universitas Negeri Semarang dengan aplikasi digital maps. Scientific Journal of Informatics, 1(2). https://doi.org/10.15294/sji.v1i2.4021
-
Nugraha, T. S. (2024). Sistem informasi eksekutif menggunakan penerapan data warehouse pada data tracer study alumni Universitas Jenderal Soedirman [Skripsi, Universitas Jenderal Soedirman]. Diakses dari https://repository.unsoed.ac.id/30817/
-
Aritonang, E., Wijoyo, S. H., & Purnomo, W. (2025). Pengembangan dashboard business intelligence untuk monitoring sistem tracer study (Studi kasus: Fakultas Ilmu Komputer Universitas Brawijaya). Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 9(13). Diakses dari https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/14795
-
Chaudhuri, S., & Dayal, U. (1997). An overview of data warehousing and OLAP technology. ACM SIGMOD Record, 26(1), 65–74. https://doi.org/10.1145/248603.248616
-
Muntean, C., & Surugiu, F. (2020). NoSQL databases in big data analytics. Journal of Computer Science and Control Systems, 13(1), 12–19. https://doi.org/10.24193/jcscs.2020.13.1.2
-
Garcia-Murillo, M., & Annabi, H. (2002). Customer knowledge management. Journal of the Operational Research Society, 53(8), 875–884. https://doi.org/10.1057/palgrave.jors.2601381
-

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish with this journal agree to the following terms:
1. Copyright Retention and Open Access License
Authors retain copyright of their work and grant the journal non-exclusive right of first publication under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
This license allows unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
2. Rights Granted Under CC BY 4.0
Under this license, readers are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, including commercial use
- No additional restrictions — the licensor cannot revoke these freedoms as long as license terms are followed
3. Attribution Requirements
All uses must include:
- Proper citation of the original work
- Link to the Creative Commons license
- Indication if changes were made to the original work
- No suggestion that the licensor endorses the user or their use
4. Additional Distribution Rights
Authors may:
- Deposit the published version in institutional repositories
- Share through academic social networks
- Include in books, monographs, or other publications
- Post on personal or institutional websites
Requirement: All additional distributions must maintain the CC BY 4.0 license and proper attribution.
5. Self-Archiving and Pre-Print Sharing
Authors are encouraged to:
- Share pre-prints and post-prints online
- Deposit in subject-specific repositories (e.g., arXiv, bioRxiv)
- Engage in scholarly communication throughout the publication process
6. Open Access Commitment
This journal provides immediate open access to all content, supporting the global exchange of knowledge without financial, legal, or technical barriers.