Rancang Bangun Infrastruktur Big Data pada Institusi Pendidikan Tinggi Multi Kampus

Authors

  • Daniel Yeri Kristiyanto Sekolah Tinggi Elektronika dan Komputer
  • Bambang Suhartono Sekolah Tinggi Elektronika dan Komputer

DOI:

https://doi.org/10.54367/means.v5i1.681

Keywords:

Sistem Informasi

Abstract

Nowadays is referred to as the era of big data where every individual or organization produces large amounts of data through various digital devices used. Higher education institutions continuously produce data and only strore it in various data formats and physical files, thus creating massive raw data. Collection of data created from a long time produces big data, so it is difficult to be treated manually or processed using conventional data processing applications. Higher education is an educational institution that always produces data from time to time continuously through various affairs in each of its parts. Multi campus institutions have physical locations that are far apart from one to another with more than one physical infrastructure. Each campus branch produces its own data, this requires a though about how to build a large data infrastructure, so that stakeholders can use various data from each branch of the campus for the analysis process of various needs of tertiary institutions. Multi campus big data infrastructure is the focus of this research, through the stages of big data sampling on multiple campuses using statistical and prototyping methods, so that data flow and data unity can be standardized in all branches of the campus by minimizing infrastructure constraints that are based on socioculture and spatial aspects.

References

I. Kristanti and N. Umamah, “Jurnal Historica THE CHARACTER-BASED MODULES AND THEIR INFLUENCE ONHISTORICAL AWARENESS OF STUDENTS OF CLASS XI MIPA 4 SMAN PASIRIAN,†Hist. Lima., vol. 3, no. 2252, pp. 78–89, 2019.

A. Dukhanov, A. Boukhanovsky, T. Sidorova, and N. Spitsyna, “Big Data and Artificial Intelligence for Digital Humanities: An International Master Program via Trans-Eurasian Universities Network,†Procedia Comput. Sci., vol. 101, pp. 449–451, 2016.

D. Y. Kristiyanto, A. Iriani, S. Yulianto, and J. Prasetyo, “Visualisasi dan Intepretasi Database Engine Website Penilai Kinerja Karyawan Berbasis Online Transaction Processing (OLTP),†in Prosiding SINTAK 2018, 2018, no. Mvc, pp. 325–332.

D. Y. Kristiyanto, B. Suhartono, and A. Wibowo, “Digital Forensic InnoDB Database Engine for Employee Performance Appraisal Application,†in E3S Web of Conferences, 2019, vol. 125, no. 201 9.

S. T. Ng, F. J. Xu, Y. Yang, and M. Lu, “A Master Data Management Solution to Unlock the Value of Big Infrastructure Data for Smart, Sustainable and Resilient City Planning,†in Procedia Engineering, 2017, vol. 196, no. June, pp. 939–947.

N. B. C. E. Jamil, I. Bin Ishak, F. Sidi, L. S. Affendey, and A. Mamat, “A Systematic Review on the Profiling of Digital News Portal for Big Data Veracity,†Procedia Comput. Sci., vol. 72, pp. 390–397, 2015.

J. Nelson, A. Berlin, J. Menold, and M. Parkinson, “The role of digital prototyping tools in learning factories,†in Procedia Manufacturing, 2020, vol. 45, no. 2019, pp. 528–533.

H. Vestad and M. Steinert, “Creating your own tools: Prototyping environments for prototype testing,†in Procedia CIRP, 2019, vol. 84, pp. 707–712.

S. Berhe, M. Maynard, and F. Khomh, “Software Release Patterns When is it a good time to update a software component?,†Procedia Comput. Sci., vol. 170, no. 2019, pp. 618–625, 2020.

L. Li et al., “An integrated hardware/software design methodology for signal processing systems,†J. Syst. Archit., vol. 93, no. April 2018, pp. 1–19, 2019.

R. Bivand and K. Krivoruchko, “Big data sampling and spatial analysis: ‘which of the two ladles, of fig-wood or gold, is appropriate to the soup and the pot?,’†Stat. Probab. Lett., vol. 136, no. xxxx, pp. 87–91, 2018.

D. Suleiman, M. Al-Zewairi, and G. Naymat, “An Empirical Evaluation of Intelligent Machine Learning Algorithms under Big Data Processing Systems,†in Procedia Computer Science, 2017, vol. 113, pp. 539–544.

F. Fagerholm, A. Hellas, M. Luukkainen, K. Kyllönen, S. Yaman, and H. Mäenpää, “Designing and implementing an environment for software start-up education: Patterns and anti-patterns,†J. Syst. Softw., vol. 146, pp. 1–13, 2018.

Published

2020-06-26

How to Cite

Kristiyanto, D. Y., & Suhartono, B. (2020). Rancang Bangun Infrastruktur Big Data pada Institusi Pendidikan Tinggi Multi Kampus. MEANS (Media Informasi Analisa Dan Sistem), 5(1), 1–7. https://doi.org/10.54367/means.v5i1.681

Issue

Section

Daftar Artikel