Digital HRM with Machine Learning Approach

Authors

Muhammad Fauzan Azhmy , Annisha Suvero Suyar , Arasy Ayu Setiamy

DOI:

10.29303/jppipa.v10iSpecialIssue.7213

Published:

2024-08-25

Issue:

Vol. 10 No. SpecialIssue (2024): In Press

Keywords:

Digital, HRM, Machine, Learning approach

Research Articles

Downloads

How to Cite

Azhmy, M. F., Suyar, A. S., & Setiamy, A. A. (2024). Digital HRM with Machine Learning Approach. Jurnal Penelitian Pendidikan IPA, 10(SpecialIssue), 18–23. https://doi.org/10.29303/jppipa.v10iSpecialIssue.7213
Crossref
Scopus
Google Scholar
Europe PMC

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Abstract

The purpose of this paper is to provide an overview of how modern resource management resolves conventional challenges in that area. Computing technology with all its specific application variants will help human performance in HR management in the contemporary era. The rapid advancement of technology and digitalization has presented a digital economy characterized by business and the trade transactions based on technology. This study aims to analyze the influence of the digital economy as measured by the Value of Electronic Money Transactions and the Value of E-Commerce Transactions on Indonesia’s economic growth. This research method is descriptive qualitative with a literature study approach. The data sources used are journal manuscripts, books, and other sources that are in accordance with the theme of this study. The data will be elaborated to get the construction of relevant thoughts and reflect an adequate analysis of computers and human resource management in this modern era. The results of the study are computing is able to carry out administrative tasks automatically; computing is able to increase employee engagement; computing can help improve the recruitment and orientation process; computing can help ensure compliance; and computing can help drive data-driven decision making.

References

Bakare, K. M. (2020). Impact of Human Resources Development on Economic Growth: An Appraisal. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3675605

Buccieri, G. P., Muniz, J., Balestieri, J. A. P., & Matelli, J. A. (2020). Expert systems and knowledge management for failure prediction to onshore pipelines: Issue to industry 4.0 implementation. Gestao e Producao, 27(3), 1–19. https://doi.org/10.1590/0104-530x5771-20

Cabrera, R. M., Ganchozo, M. L., Oswaldo, R. S., Wilfredo, R., Bujaico, R., Samaniego, H. H., & Fredy, J. (2022). Impact Of Machine Learning In Human Resource Management: Towards The Modernization Of Leadership. Journal of Positive School Psychology, 6(2), 290–299. Retrieved from https://journalppw.com/index.php/jpsp/article/view/10210

Chytiri, A.-P. (2019). Human Resource Managers’ Role in the Digital Era. SPOUDAI Journal of Economic and Business, 69(1), 62–72. Retrieved from https://dora.dmu.ac.uk/server/api/core/bitstreams/ea2d44b0-1211-4672-9c14-b594046a1ac1/content

Cresswell, J. (2012). Research Design : Qualitative, Quantitavive and Miixed Methods Approach. Sage Publication.

Fischer, E., & Guzel, G. T. (2023). The case for qualitative research. Journal of Consumer Psychology, 33(1), 259–272. https://doi.org/10.1002/jcpy.1300

Jia, Q., Guo, Y., Li, R., Li, Y., & Chen, Y. (2018). A conceptual artificial intelligence application framework in human resource management. Proceedings of the International Conference on Electronic Business (ICEB), 106–114. Retrieved from https://aisel.aisnet.org/iceb2018/91/

Kalia, P., & Mishra, G. (2023). Role of artificial intelligence in Re-inventing human resource management. In The Adoption and Effect of Artificial Intelligence on Human Resources Management, Part B (pp. 221–234). Emerald Publishing Limited. https://doi.org/10.1108/978-1-80455-662-720230013

Kalsum, U. (2022). Pengenalan Kecerdasan Buatan (Artificial Intelligence) Kepada Para Remaja. Procedia Computer Science, 166, 310–314. Retrieved from https://eprints.binadarma.ac.id/15964/

Kehoe, R. R., Collings, D. G., & Cascio, W. F. (2023). Simply the best? Star performers and high-potential employees: Critical reflections and a path forward for research and practice. Personnel Psychology, 76(2), 585–615. https://doi.org/10.1111/peps.12558

Lombardi, M., Pascale, F., & Santaniello, D. (2021). Internet of things: A general overview between architectures, protocols and applications. Information, 12(2), 87. https://doi.org/10.3390/info12020087

Mazurchenko, A., & Maršíková, K. (2019). Digitally-powered human resource management: Skills and roles in the digital era. Acta Informatica Pragensia, 8(2), 72–86. https://doi.org/10.18267/j.aip.125

Mosca, M. (2020). Digitalization of HRM: A study of success factors and consequences in the last decade [University of Twente]. Retrieved from https://purl.utwente.nl/essays/82872

Mouha, R. A. R. (2021). Internet of things (IoT). Journal of Data Analysis and Information Processing, 9(02), 77. https://doi.org/10.4236/jdaip.2021.92006

OECD. (2021). Artificial Intelligence, Machine Learning and Big Data in Finance: Opportunities, Challenges, and Implications for Policy Makers. OECD Business and Finance Outlook 2020 : Sustainable and Resilient Finance. Retrieved from https://shorturl.asia/z6kEV

Prakash, N., Krishna, G., & Mores, G. (2019). Digitalization of HRM Practice in the Present Scenario. International Journal of Research in Management Studies, 4(1), 1–5. Retrieved from https://shorturl.asia/NL3C2

Saibene, A., Assale, M., & Giltri, M. (2021). Expert systems: Definitions, advantages and issues in medical field applications. Expert Systems with Applications, 177, 114900. https://doi.org/10.1016/j.eswa.2021.114900

Sakka, F., & El Hadi El Maknouzi, M. (2022). Human Resource Management in the Era of Artificial Intelligence: Future Hr Work Practices, Anticipated Skill Set, Financial and Legal Implications. Academy of Strategic Management Journal, 21(S1), 1–14. Retrieved from https://sdbindex.com/Documents/index/00000155/00001-49257

Setiawan, T., & Padmaningrum, D. (2020). Toward the Design of Village Information Systems As a Villager Communication Medium. International Journal Of Multi Science, 1(4), 1–6. Retrieved from https://multisciencejournal.com/index.php/ijm/article/view/20

Setiawan, T., & Putro, F. H. A. (2021). Optimasi Ekonomi Less Contact Melalui Teknik Digital Marketing Pada Industri Umkm Di Kecamatan Simo Kabupaten Boyolali. Jurnal Ekonomi, Sosial, & Humaniora, 03(04), 33–48. Retrieved from https://www.jurnalintelektiva.com/index.php/jurnal/article/view/574%0Ahttps://www.jurnalintelektiva.com/index.php/jurnal/article/download/574/483

Siregar, H., Setiawan, W., & Dirgantari, P. D. (2020). Isu Proses Bisnis Berbasis Artificial Intelligence untuk Menyosong Era Industri 4.0. Jurnal Bisnis Strategi, 29(2), 89–100. https://doi.org/10.14710/jbs.29.2.89-100

Strohmeier, S. (2020). Digital human resource management: A conceptual clarification. German Journal of Human Resource Management, 34(3), 345–365. https://doi.org/10.1177/2397002220921131

Tomaszewski, L. E., Zarestky, J., & Gonzalez, E. (2020). Planning qualitative research: Design and decision making for new researchers. International Journal of Qualitative Methods, 19, 1609406920967174. https://doi.org/10.1177/1609406920967174

Wagner, W. P. (2017). Trends in expert system development: A longitudinal content analysis of over thirty years of expert system case studies. Expert Systems with Applications, 76, 85–96. https://doi.org/10.1016/j.eswa.2017.01.028

Wijaya, H. (2018). Analisis Data Kualitatif Model Spradley (Etnografi). Sekolah Tinggi Theologia Jaffray, 31, 1–10. Retrieved from https://www.researchgate.net/publication/323557072

Zhang, J., & Chen, Z. (2023). Exploring Human Resource Management Digital Transformation in the Digital Age. Journal of the Knowledge Economy, 29. https://doi.org/10.1007/s13132-023-01214-y

Author Biographies

Muhammad Fauzan Azhmy, Universitas Harapan Medan

Annisha Suvero Suyar, Universitas Harapan Medan

Arasy Ayu Setiamy, Universitas Harapan Medan

License

Copyright (c) 2024 Muhammad Fauzan Azhmy, Annisha Suvero Suyar, Arasy Ayu Setiamy

Creative Commons License

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

Authors who publish with Jurnal Penelitian Pendidikan IPA, agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License (CC-BY License). This license allows authors to use all articles, data sets, graphics, and appendices in data mining applications, search engines, web sites, blogs, and other platforms by providing an appropriate reference. The journal allows the author(s) to hold the copyright without restrictions and will retain publishing rights without restrictions.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in Jurnal Penelitian Pendidikan IPA.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).