Tren Penggunaan Framework COBIT, ITIL, dan ISO 27001 Pada Rentang Tahun 2014-2018 di Indonesia

Nur Rochmania, Indri Sudanawati Rozas, Ilham Ilham

Abstract


The use of Information Technology (IT) frameworks from year to year in Indonesia has shown an increase. However, there is not much research on the use of IT frameworks. The research on IT frameworks can be used by a company to analyze trends in the use of frameworks in Indonesia. That way, it can help a company consider choosing a framework to use. The IT frameworks discussed in this study are COBIT, ITIL, and ISO 27001. Data related to research IT frameworks taken in the 2014-2018 period. Data collection through the Google Scholar web search engine using the Publish or Perish software. The data obtained were analyzed using descriptive quantitative methods. The results of this study can use to determine the use of the IT framework in Indonesia. The amount of raw data obtained from the data collection process was 5,708 data with Authors, Title, Years, and Publisher variables. Research data on titles and keywords obtained in the Indonesian domain amounted to 754 and overseas amounted to 194.  From the research results, it can conclude that the most widely used framework is the COBIT framework, with a percentage of 69.3% in the Indonesian and 58.7% in the foreign domain.


Keywords


COBIT; Google Scholar; ISO 27001; ITIL; Publish or Perish

Full Text:

PDF

References


Aguiar, J., Pereira, R., Vasconcelos, J. B., & Bianchi, I. (2018). An Overlapless Incident Management Maturity Model For Multi-Framework Assestment (ITIL, COBIT, CMMI-SVC). Interdisciplinary Journal of Information, Knowledge, and Management, 13(1), 137–163.

Aprilinda, Y., Puspa, A. K., & Affandy, F. N. (2019). The Use of ISO and COBIT for IT Governance Audit. Journal of Physics: Conference Series, 1381(1), 0–6.

Azeroual, O., Saake, G., & Abuosba, M. (2018). Data Quality Measures and Data Cleansing for Research Information Systems. Journal of Digital Information Management, 16(1), 12–21.

Ertaş, M., & Kozak, M. (2020). Publish or perish: The proportion of articles versus additional sections in tourism and hospitality journals. Journal of Hospitality and Tourism Management, 43(1), 149–156.

Hara, S., Nitanda, A., & Maehara, T. (2019). Data cleansing for models trained with SGD. Advances in Neural Information Processing Systems, 32(1), 1–23.

Harzing, A. W. (2019). Two new kids on the block: How do Crossref and Dimensions compare with Google Scholar, Microsoft Academic, Scopus and the Web of Science? Scientometrics, 120(1), 341–349.

Huygh, T., & De Haes, S. (2019). Investigating IT Governance through the Viable System Model. Information Systems Management, 36(2), 168–192.

Karthikeyan, T., Sekaran, K., Ranjith, D., Vinoth kumar, V., & Balajee, J. M. (2019). Personalized content extraction and text classification using effective web scraping techniques. International Journal of Web Portals, 11(2), 41–52.

Mardin, H., Baharuddin, B., & Nane, L. (2020). Pelatihan Cara Menulis Sitasi Dan Daftar Pustaka Jurnal Format Apa Style Menggunakan Aplikasi Mendeley. Abidas, 1(1), 1–6.

Martín-Martín, A., Thelwall, M., Orduna-Malea, E., & Delgado López-Cózar, E. (2020). Google Scholar, Microsoft Academic, Scopus, Dimensions, Web of Science, and OpenCitations’ COCI: a multidisciplinary comparison of coverage via citations. In Scientometrics (Vol. 2).

Nasution, L. M. (2017). Statiskik Deskriptif. Jurnal Hikmah, 14(1), 49–55.

Sugiyono. (2017). Metode Penelitian Bisnis: Pendekatan Kuantitatif, Kualitatif, Kombinasi, dan R&D. Alfabeta.

Suryawan, A. D., & Veronica. (2018). Information Technology Service Performance Management Using COBIT and ITIL Frameworks : A Case Study. Proceedings of 2018 International Conference on Information Management and Technology, ICIMTech 2018, 223–228.

Verheggen, K., Ræder, H., Berven, F. S., Martens, L., Barsnes, H., & Vaudel, M. (2020). Anatomy and evolution of database search engines—a central component of mass spectrometry based proteomic workflows. Mass Spectrometry Reviews, 39(3), 292–306.

Widiastuti, N. I., Rainarli, E., & Dewi, K. E. (2017). Peringkasan dan Support Vector Machine pada Klasifikasi Dokumen. Jurnal Infotel, 9(4), 416–421.


Article Metrics

Abstract view : 0 times
PDF - 0 times

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

 

  Statistic Pengunjung Edumatic

Creative Commons License

Edumatic: Jurnal Pendidikan Informatika is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.