Pengaruh Pemahaman Predictive Analytics Berbasis AI terhadap Optimalisasi Perencanaan Sumber Daya Manusia dalam Mendukung Transformasi Digital pada PT Moklet Teknologi Intidaya
Keywords:
Predictive Analytics, Artificial Intelligence, Digital Human Resource Planning, PLS-SEM, HR OptimizationAbstract
This study aims to analyze the effect of understanding Predictive Analytics based on Artificial Intelligence (AI) on the optimization of Human Resource (HR) planning in digital form at PT Moklet Teknologi Intidaya. This research employs a quantitative approach using a saturated sampling technique involving all 40 employees as respondents. Data were collected through a Likert-scale questionnaire, which was tested for validity and reliability. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that employees’ understanding of AI-based Predictive Analytics has a positive and significant effect on the optimization of digital HR planning, with a path coefficient of 0.862, t-statistic of 20.036, and p-value < 0.05. These findings confirm that digital literacy and AI competence are important factors in improving the accuracy of HR planning and supporting data-driven strategic decision-making in growing companies. In addition, the study highlights that the integration of predictive analytics can assist organizations in identifying workforce needs more efficiently, reducing potential planning errors, and strengthening organizational readiness in facing digital transformation challenges. The findings also emphasize the importance of continuous employee training and technological adaptation to ensure sustainable HR management practices. This study contributes to the development of digital human resource management literature by providing empirical evidence regarding the role of employees' understanding of AI-based predictive analytics in optimizing workforce planning within a growing technology company.
References
Alhamad, A., Alshurideh, M., Alomari, K., Al Kurdi, B., Alzoubi, H., Hamouche, S., & Al-Hawary, S. (2022). The effect of electronic human resources management on organizational health of telecommunications companies in Jordan. International Journal of Data and Network Science, 6(2), 429–438. https://doi.org/10.5267/j.ijdns.2021.12.011
Bositkhanova, N., & Dadaboyev, S. M. U. (2025). Revolutionizing workforce planning: the strategic role of AI in HR strategy. Discover Global Society, 3(1). https://doi.org/10.1007/s44282-025-00252-y
Cheung, G. W., Cooper-Thomas, H. D., Lau, R. S., & Wang, L. C. (2024). Reporting reliability, convergent and discriminant validity with structural equation modeling: A review and best-practice recommendations. In Asia Pacific Journal of Management (Vol. 41, Number 2). Springer US. https://doi.org/10.1007/s10490-023-09871-y
Darmalaksana, W. (2020). M. P. K. S. P. dan S., Bandung, L. P.-P. D. L. U. S. G. D., & 1–6. (2020). Metode Penelitian Kualitatif Studi Pustaka dan Studi Bandung, Lapangan. Pre-Print Digital Library UIN Sunan Gunung Djati 1.
Edumadze, J. K. E., & Govender, D. W. (2024). The community of inquiry as a tool for measuring student engagement in blended massive open online courses (MOOCs): a case study of university students in a developing country. Smart Learning Environments, 11(1). https://doi.org/10.1186/s40561-024-00306-9
Gefen, D., Straub, D., & Boudreau, M.-C. (2000). Structural Equation Modeling and Regression: Guidelines for Research Practice. Communications of the Association for Information Systems, 4(October). https://doi.org/10.17705/1cais.00407
Hair Jr et al. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook (p. 197). Springer Nature. In Structural Equation Modeling: A Multidisciplinary Journal (Vol. 30, Number July).
Hasanah, U. (2026). TRANSFORMASI DIGITAL DALAM HUMAN RESOURCE MANAGEMENT : PENDEKATAN PREDICTIVE ANALYTICS. 2, 212–218.
Hermawan, S., & Hariyanto, W. (2022). Buku Ajar Metode Penelitian Bisnis (Kuantitatif Dan Kualitatif ). In Buku Ajar Metode Penelitian Bisnis (Kuantitatif Dan Kualitatif ). https://doi.org/10.21070/2022/978-623-464-047-2
Hong, N. T. H., Hanh, T. T., Anh, N. Q., Anh, D. N., Ngoc, T. M., & Nhi, N. D. L. (2024). Green Human Resources Management and employees’ green behavioral intention: the role of individual green values and corporate social responsibility. Cogent Business and Management, 11(1). https://doi.org/10.1080/23311975.2024.2386464
Kurniati, I., Winarno, H., & Yuliyanti, D. (2023). Pemanfaatan Algoritma Neural Network Untuk Predictive Analytic Angka Buta Huruf Di Indonesia. Jeis: Jurnal Elektro Dan Informatika Swadharma, 3(2), 94–104. https://doi.org/10.56486/jeis.vol3no2.364
LutfianI, N., Widayanti, R., Sembiring, I., Rahardja, U., Iwan, Setyawan, & Setiawan, A. (2025). Exploring the relationship between artificial intelligence and Islamic finance. Artificial Intelligence and Islamic Finance, 19(1), 77–87. https://doi.org/10.4324/9781003171638-6
Muhamad Farhan Ali, Rezha Fahrullah, & Didin Hikmah Perkasa. (2024). Strategi Penerapan Kecerdasan Buatan (AI) Dalam Mengelola Manajemen Sumber Daya Manusia Internasional (IHRM). Jurnal Ekonomi Manajemen Sistem Informasi, 6(2), 1121–1129. https://doi.org/10.38035/jemsi.v6i2.3527
Namazov, G., Tukhtaeva, N., Ernazarov, M., & Meylikulov, S. (2025). Role of AI-Powered Talent Analytics and Predictive Analytics in Enhancing Operational Resilience of Tech Enterprises. International Academic Journal of Science and Engineering, 12(4), 396–405. https://doi.org/10.71086/IAJSE/V12I4/IAJSE12107
Nisa, S. K. (2025). Strategi transformasi digital dalam meningkatkan daya saing dan kinerja perusahaan di era artificial intelligence. 3, 1634–1640.
Nishitha Reddy Nalla. (2024). AI-Driven Predictive Analytics for Workforce Planning and Optimization. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 10(4), 349–353. https://doi.org/10.32628/cseit2477112
Raharjo, B. (2021). Penerapan Artificial Intelegent Dalam Bisnis. In Yayasan Prima Agus Teknik. http://penerbit.stekom.ac.id/index.php/yayasanpat/article/view/149
Seočanac, M. (2024). PLS-SEM: A hidden gem in tourism research methodology. Menadzment u Hotelijerstvu i Turizmu, 12(1), 115–131. https://doi.org/10.5937/menhottur2400005s
Tedy Roberto, Lena Nofelia, Tati Murni, Sufyarma Marsidin, & Nellitawati. (2022). Perencanaan Sumber Daya Manusia. EduInovasi: Journal of Basic Educational Studies, 5(1), 161–170. https://doi.org/10.47467/edu.v5i1.5885
Tilahun, M., Berhan, E., & Tesfaye, G. (2023). Determinants of consumers’ purchase intention on digital business model platform: evidence from Ethiopia using partial least square structural equation model (PLS-SEM) technique. Journal of Innovation and Entrepreneurship, 12(1). https://doi.org/10.1186/s13731-023-00323-x
Walker. (1980). Walker-Report-1980.pdf (p. Report on the Interchange of Intelligence between). Belfast: Royal Ulster Constabulary.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Dian Riska Trianjani, Misbahul Munir, Sayyidah Auliya, Niki Puspitasari
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
