Pengembangan Dashboard Interaktif Berbasis Big Data Akademik untuk Mendukung Pengambilan Keputusan Manajemen di Perguruan Tinggi
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Abstract
Era transformasi digital di sektor pendidikan tinggi menekankan perlunya pengolahan data akademik yang adaptif untuk memfasilitasi pengambilan keputusan manajerial yang presisi, andal, dan didukung fakta empiris. Lonjakan volume data, keragaman format dari sistem akademik, keuangan, sumber daya manusia, serta mekanisme penjaminan mutu telah mengungkap keterbatasan pendekatan pengolahan konvensional yang lambat dan fragmentaris. Studi ini merancang serta memvalidasi dashboard interaktif berbasis big data akademik yang mengubah data mentah menjadi representasi visual strategis guna memperkuat proses decision-making di institusi perguruan tinggi.
Metodologi research and development diterapkan secara bertahap, mencakup identifikasi kebutuhan pengguna akhir, konseptualisasi arsitektur data terintegrasi, pembangunan prototipe dashboard, serta pengujian komprehensif terhadap fungsionalitas dan penerimaan pengguna. Sumber data internal diekstrak, ditransformasi, dan dimuat melalui pipeline ETL ke gudang data sentral, menghasilkan visualisasi dinamis untuk indikator kinerja krusial seperti demografi mahasiswa, metrik dosen, pencapaian pembelajaran, serta dinamika kelulusan. Pengukuran efektivitas dilakukan via uji fungsi dan survei manajemen, menargetkan aspek usability, akurasi informasi, serta dampak terhadap efisiensi keputusan.
Temuan utama mengindikasikan peningkatan substansial dalam pemahaman holistik kondisi akademik secara waktu nyata, akselerasi proses analitik strategis, serta minimisasi ketergantungan pada mekanisme pelaporan statis manual. Inovasi ini berkontribusi pada ekosistem sistem pendukung keputusan di ranah pendidikan tinggi melalui optimalisasi big data akademik dan teknik visualisasi adaptif, menawarkan blueprint praktis bagi perguruan tinggi lain dalam membangun governance data-centric.
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References
A. Stojanov and B. K. Daniel, “A decade of research into the application of big data and analytics in higher education: A systematic review of the literature,” Educ. Inf. Technol. (Dordr)., vol. 29, no. 5, pp. 5807–5831, Apr. 2024, doi: 10.1007/s10639-023-12033-8.
D. Ifenthaler, · Jane, Y.-K. Yau, D. Ifenthaler, and Y.-K. Yau, “Utilising learning analytics to support study success in higher education: a systematic review,” SpringerD Ifenthaler, JYK YauEducational Technology Research and Development, 2020•Springer, vol. 68, no. 4, pp. 1961–1990, Aug. 2020, doi: 10.1007/S11423-020-09788-Z.
R. Sharda, D. Delen, and E. Turban, “Analytics, data science, & artificial intelligence: Systems for decision support,” 2021, Accessed: Jan. 10, 2026. [Online]. Available: https://www.pearson.com/content/dam/one-dot-com/one-dot-com/us/en/files/Global/Pearson-2022-IT-International-Catalogue.pdf
V. C. Chen, H., Chiang, R. H. L., & Storey, “Business Intelligence and Analytics from Big Data to Healthcare,” Handbook of Intelligent Healthcare Analytics: Knowledge Engineering with Big Data Analytics, vol. 36, no. 4, pp. 115–145, 2022, doi: 10.1002/9781119792550.ch6.
B. K. Daniel and R. J. Butson, “The Rise of Big Data and Analytics in Higher Education,” The Analytics Process, pp. 113–126, Mar. 2017, doi: 10.1201/9781315161501-5/RISE-BIG-DATA-ANALYTICS-HIGHER-EDUCATION-BEN-DANIEL-RUSSELL-BUTSON.
O. Viberg, M. Hatakka, O. Bälter, and A. Mavroudi, “The current landscape of learning analytics in higher education,” Comput. Human Behav., vol. 89, pp. 98–110, Dec. 2018, doi: 10.1016/J.CHB.2018.07.027.
“S. Alammary, J. Sheard, and A. Carbone, Data integration challenges in higher education analytics, IEEE Transactions on Education, vol. 64, no. 3, pp. 231–239, 2021. - Penelusuran Google.” Accessed: Jan. 10, 2026. [Online]. Available: https://www.google.com/search?sca_esv=a6db2d49f6f48867&sxsrf=ANbL-n4eh5eOuXBmsCU2q9LXYeq9TRop4A:1768046582181&q=S.+Alammary,+J.+Sheard,+and+A.+Carbone,+Data+integration+challenges+in+higher+education+analytics,+IEEE+Transactions+on+Education,+vol.+64,+no.+3,+pp.+231%E2%80%93239,+2021.&sa=X&ved=2ahUKEwjwtujj9oCSAxX8yzgGHVy2EjYQgwN6BAgWEAE&biw=1440&bih=812&dpr=1&aic=0
F. Kassambara, A., & Mundt, “xtract and Visualize the Results of Multivariate Data Analyses,” Retrieved from https://cran.r-project.org/package=factoextra, 2020.
H. Watson, B. W.- Computer, and undefined 2007, “The current state of business intelligence,” ieeexplore.ieee.orgHJ Watson, BH WixomComputer, 2007•ieeexplore.ieee.org, Accessed: Jan. 10, 2026. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/4302625/
A. Nugroho, … P. S.-… S. on I., and undefined 2022, “Usability evaluation methods of mobile applications: A systematic literature review,” ieeexplore.ieee.org, Accessed: Jan. 10, 2026. [Online]. Available: https://ieeexplore.ieee.org/abstract/document/9944401/
K. Sedig and P. Parsons, “Design of Visualizations for Human-Information Interaction,” 2022, doi: 10.1007/978-3-031-02602-7.
“W. Ouyang, “Interactive data visualization for... - Google Scholar.” Accessed: Jan. 10, 2026. [Online]. Available: https://scholar.google.com/scholar?hl=id&as_sdt=0%2C5&q=W.+Ouyang%2C+%E2%80%9CInteractive+data+visualization+for+big+data+analytics%2C&btnG=
R. Pressman, “Software engineering: a practitioner’s approach,” 2005, Accessed: Jan. 10, 2026. [Online]. Available: https://books.google.com/books?hl=id&lr=&id=bL7QZHtWvaUC&oi=fnd&pg=PA1&dq=R.+S.+Pressman+and+B.+Maxim,+Software+Engineering:+A+Practitioner%E2%80%99s+Approach,+9th+ed.,+2020.&ots=O9zf5PvN4g&sig=pnBrC_F0_mJXMMpRZmJ9i-_Iclw
R. Pressman, “Software engineering: a practitioner’s approach,” 2005, Accessed: Jan. 10, 2026. [Online]. Available: https://books.google.com/books?hl=id&lr=&id=bL7QZHtWvaUC&oi=fnd&pg=PA1&dq=R.+S.+Pressman+and+B.+Maxim,+Software+Engineering:+A+Practitioner%E2%80%99s+Approach,+9th+ed.,+New+York,+NY,+USA:+McGraw-Hill,+2020.&ots=O9zf5PuPbj&sig=ZJcLGI-_YwQol3Jy0BvLk3Q82ds
by Rayan Alshamrani et al., “Enhancing the Shared Decision-Making Experience of Multiple Sclerosis Via Model-Driven Decision Support,” 2023, Accessed: Jan. 10, 2026. [Online]. Available: https://search.proquest.com/openview/175d88474982b9838429574e30b3d254/1?pq-origsite=gscholar&cbl=18750&diss=y
J. Creswell, M. I.-J. of G. and Family, and undefined 2025, “A process for conducting mixed methods data analysis,” Wiley Online Library, vol. 26, no. 1, pp. 4–11, Jan. 2025, doi: 10.1002/JGF2.736.
K. Schwaber, J. S.-A. April, and undefined 2021, “The scrum guide. 2020,” mthi.vnK Schwaber, J SutherlandAccessed April, 2021•mthi.vn, Accessed: Jan. 10, 2026. [Online]. Available: https://mthi.vn/wp-content/uploads/2021/01/20210115-SCRUM-GUIDE-2020-VIE-THI.pdf
J. Vom Brocke, R. Winter, A. H.-… for I. Systems, and undefined 2020, “Special issue editorial–accumulation and evolution of design knowledge in design science research: a journey through time and space,” aisel.aisnet.orgJ Vom Brocke, R Winter, A Hevner, A MaedcheJournal of the Association for Information Systems, 2020•aisel.aisnet.org, Accessed: Jan. 10, 2026. [Online]. Available: https://aisel.aisnet.org/jais/vol21/iss3/9/
K. Peffers, M. Rothenberger, T. Tuunanen, and R. Vaezi, “Design science research evaluation,” Springer, vol. 7286 LNCS, pp. 398–410, 2012, doi: 10.1007/978-3-642-29863-9_29.
A. Dresch, D. Lacerda, J. A. J.-D. science research: A, and undefined 2014, “Design science research,” Springer, pp. 67–102, 2015, doi: 10.1007/978-3-319-07374-3_4.
A. Walha, F. Ghozzi, F. G.-J. of Supercomputing, and undefined 2024, “Data integration from traditional to big data: main features and comparisons of ETL approaches.,” search.ebscohost.com, Accessed: Jan. 10, 2026. [Online]. Available: https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=09208542&AN=180106931&h=dYseJ98sKaiTKRM0502wTPn7CMXc%2FKnH%2FxuDrd1aEBZjB7vnnYU1qM1ZUCQE1M7zxLLYExmAnQO4TMBdyE%2FVdw%3D%3D&crl=c
K. Ansari, M. G. C. I. Systems, and undefined 2023, “Big data analytics capability and firm performance: meta-analysis,” Taylor & Francis, vol. 63, no. 6, pp. 1477–1494, 2023, doi: 10.1080/08874417.2023.2170300.
K. Sedig and P. Parsons, “Design of visualizations for human-information interaction: A pattern-based framework,” 2022, Accessed: Jan. 10, 2026. [Online]. Available: https://books.google.com/books?hl=id&lr=&id=RYFyEAAAQBAJ&oi=fnd&pg=PR1&dq=M.+Sedig+and+P.+Parsons,+%E2%80%9CVisual+analytics+design,&ots=4_AMzR30Hz&sig=kp_egde8VBphF3YPMB0dAcIP91A
N. S.-: J. I. Komputer, S. I. dan, and undefined 2025, “Perancangan Business Intelligence Dashboard Sales Performance,” ejournal.cyber-univ.ac.id, vol. 2, no. 2, 2025, Accessed: Jan. 11, 2026. [Online]. Available: https://ejournal.cyber-univ.ac.id/index.php/innotech/article/view/86
C. Lennerholt, J. Van Laere, and E. Söderström, “User-related challenges of self-service business intelligence,” Taylor & Francis, vol. 38, no. 4, pp. 309–323, 2021, doi: 10.1080/10580530.2020.1814458.
P. W. Jordan, “An introduction to usability,” An Introduction to Usability, Aug. 2020, doi: 10.1201/9781003062769/INTRODUCTION-USABILITY-PATRICK-JORDAN.
K. F.-I. J. of A. I. System and undefined 2015, “Decision support system (DSS) in higher education system,” academia.edu, Accessed: Jan. 11, 2026. [Online]. Available: https://www.academia.edu/download/40406690/ijais15-451366_2.pdf