Integrating Artificial Intelligence in Human Resource Management: A SmartPLS Approach for Entrepreneurial Success

Dewi Sri Surya Wuisan; Richard Andre Sunardjo; Qurotul Aini; Natasya Aprila Yusuf; Untung Rahardja

doi:10.34306/att.v5i3.355

Authors

Dewi Sri Surya Wuisan Pelita Harapan University
Richard Andre Sunardjo University of Raharja
Qurotul Aini Rey Incorporation
Natasya Aprila Yusuf Pandawan Incorporation
Untung Rahardja Universiti Teknologi Malaysia

DOI:

https://doi.org/10.34306/att.v5i3.355

Keywords:

Artificial Intelligence, Entrepreneurship, Human Resource Management, SmartPLS, Performance Management

Abstract

The primary focus of this research is to examine the pivotal role of Artificial Intelligence (AI) in driving business transformation, with a specific emphasis on its impact within the realm of human resource management (HR). The study seeks to assess the substantial influence brought about by the incorporation of AI in HR. Online data collection involved 110 respondents with professional backgrounds in HR. In pursuit of enhancing entrepreneurial success, the research adopts the Smart Partial Least Square (Smart PLS) approach to seamlessly integrate artificial intelligence into HR management. The analysis using Smart PLS delves into the examination of AI's effects on the recruitment process, employee development, and performance management. The findings of the research reveal that the utilization of AI in HR significantly expedites processes, enhances decision accuracy, and positively contributes to the attainment of entrepreneurial objectives. The practical implications of these outcomes are thoroughly discussed, and potential avenues for future research are outlined. This not only provides valuable insights for stakeholders but also offers guidance on optimizing the application of AI in the context of human resource management.

References

N. Lutfiani, S. Wijono, U. Rahardja, A. Iriani, and E. A. Nabila, “Artificial Intelligence Based on Recommendation System for Startup Matchmaking Platform,” in 2022 IEEE Creative Communication and Innovative Technology (ICCIT), 2022, pp. 1–5.

U. Rahardja, A. Sari, A. H. Alsalamy, S. Askar, A. H. R. Alawadi, and B. Abdullaeva, “Tribological Properties Assessment of Metallic Glasses Through a Genetic Algorithm Optimized Machine Learning Model,” Met. Mater. Int., pp. 1–11, 2023.

R. Widayanti, M. H. R. Chakim, C. Lukita, U. Rahardja, and N. Lutfiani, “Improving Recommender Systems using Hybrid Techniques of Collaborative Filtering and Content Based Filtering,” J. Appl. Data Sci., vol. 4, no. 3, pp. 289–302, 2023.

N. Hussain and G. A. Pangilinan, “Robotics and Automation with Artificial Intelligence Improving Efficiency and Quality,” Aptisi Trans. Technopreneursh., vol. 5, no. 2, pp. 176–189, 2023.

A. Asmolov and A. Ledentsov, “Industry Modern A Solution for Sustainable Business Performance’s Technology Challenges,” Aptisi Trans. Technopreneursh., vol. 4, no. 3, pp. 306–312, 2022.

N. Lutfiani, S. Wijono, U. Rahardja, A. Iriani, Q. Aini, and R. A. D. Septian, “A bibliometric study Recommendation based on artificial intelligence for ilearning education,” Aptisi Trans. Technopreneursh., vol. 5, no. 2, pp. 109–117, 2023.

K. Arora and A. S. Bist, “Artificial intelligence based drug discovery techniques for covid 19 detection,” Aptisi Trans. Technopreneursh., vol. 2, no. 2, pp. 120–126, 2020.

S. Kosasi, C. Lukita, M. H. R. Chakim, A. Faturahman, and D. A. R. Kusumawardhani, “The Influence of Digital Artificial Intelligence Technology on Quality of Life with a Global Perspective,” Aptisi Trans. Technopreneursh., vol. 5, no. 3, pp. 24–34, 2023.

I. Khong, N. A. Yusuf, A. Nuriman, and A. B. Yadila, “Exploring the Impact of Data Quality on Decision Making Processes in Information Intensive Organizations,” APTISI Trans. Manag., vol. 7, no. 3, pp. 253–260, 2023.

B. Bhima, A. R. A. Zahra, T. Nurtino, and M. Z. Firli, “Enhancing Organizational Efficiency through the Integration of Artificial Intelligence in Management Information Systems,” APTISI Trans. Manag., vol. 7, no. 3, pp. 282–289, 2023.

E. Sulistyaningsih, “Improving Human Resources Technology Innovation as a Business Growth Driver in the Society 5.0 Era,” ADI J. Recent Innov., vol. 4, no. 2, pp. 149–159, 2023.

S. Pranata, K. Hadi, M. H. R. Chakim, Y. Shino, and I. N. Hikam, “Business Relationship in Business Process Management and Management with the Literature Review Method,” ADI J. Recent Innov., vol. 5, no. 1Sp, pp. 45–53, 2023.

Y. Pan and L. Zhang, “Roles of artificial intelligence in construction engineering and management A critical review and future trends,” Autom. Constr., vol. 122, p. 103517, 2021.

T. Ahmad et al., “Energetics Systems and artificial intelligence Applications of industry 4.0,” Energy Reports, vol. 8, pp. 334–361, 2022.

X. Lin, R. Z. Wu, Y. T. Lim, J. Han, and S. C. Chen, “Understanding the sustainable usage intention of mobile payment technology in Korea Cross countries comparison of Chinese and Korean users,” Sustain., vol. 11, no. 19, pp. 1–23, 2019, doi: 10.3390/su11195532.

J. Ren et al., “Matching algorithms Fundamentals, applications and challenges,” IEEE Trans. Emerg. Top. Comput. Intell., vol. 5, no. 3, pp. 332–350, 2021.

J. Moscato, “Evaluating Organizational Performance Using SmartPLS A Management Perspective,” APTISI Trans. Manag., vol. 7, no. 3, pp. 273–281, 2023.

Q. Aini, E. P. Harahap, and F. Faradilla, “The effects of sales reports business intelligence on employee performance,” Aptisi Trans. Manag., vol. 4, no. 1, pp. 83–91, 2020.

N. P. L. Santoso, R. A. Sunarjo, and I. S. Fadli, “Analyzing the Factors Influencing the Success of Business Incubation Programs A SmartPLS Approach,” ADI J. Recent Innov., vol. 5, no. 1, pp. 60–71, 2023.

S. George, H. H. Lathabai, T. Prabhakaran, and M. Changat, “A framework for inventor collaboration recommendation system based on network approach,” Expert Syst. Appl., vol. 176, p. 114833, 2021.

A. Sutarman, U. Rahardja, F. P. Oganda, S. Millah, and N. N. Azizah, “The Role of Information Technology in Empowering the Creative Economy for Sustainable Tourism,” Aptisi Trans. Technopreneursh., vol. 5, no. 2sp, pp. 175–185, 2023.

T. Handra and V. P. K. Sundram, “The Effect of Human Resource Information Systems (HRIS) and Artificial Intelligence on Defense Industry Performance,” IAIC Trans. Sustain. Digit. Innov., vol. 4, no. 2, pp. 155–163, 2023.

K.-Y. Tang, C.-Y. Chang, and G.-J. Hwang, “Trends in artificial intelligence supported e learning A systematic review and co citation network analysis (1998–2019),” Interact. Learn. Environ., vol. 31, no. 4, pp. 2134–2152, 2023.

M. Hardini, R. A. Sunarjo, M. Asfi, M. H. R. Chakim, and Y. P. A. Sanjaya, “Predicting Air Quality Index using Ensemble Machine Learning,” ADI J. Recent Innov., vol. 5, no. 1Sp, pp. 78–86, 2023.

S. S. Khanal, P. W. C. Prasad, A. Alsadoon, and A. Maag, “A systematic review machine learning based recommendation systems for e learning,” Educ. Inf. Technol., vol. 25, pp. 2635–2664, 2020.

B. Domini, A. S. Dewi, and G. P. Cesna, “The Effects of Artificial Intelligence (AI) on Company Performance Including the Value of AI based Business Transformation Initiatives,” IAIC Trans. Sustain. Digit. Innov., vol. 5, no. 1, pp. 24–38, 2023.

A. S. Bist, B. Rawat, A. G. Prawiyogi, N. Septiani, M. Fakhrezzy, and D. B. Saputra, “AI Enabled Blockchain for Supply Chain in Agriculture,” in 2022 IEEE Creative Communication and Innovative Technology (ICCIT), 2022, pp. 1–5.

A. S. Panjaitan, U. Rahardja, Q. Aini, N. P. L. Santoso, and D. Apriliasari, “The management innovation of kuliah kerja praktek (kkp),” APTISI Trans. Manag., vol. 6, no. 1, pp. 62–73, 2022.

A. Ruangkanjanases, A. Khan, O. Sivarak, U. Rahardja, S.-W. Chien, and S.-C. Chen, “The Magic of Brand Experience A Value Co creation Perspective of Brand Equity on Short form Video Platforms,” Emerg. Sci. J., vol. 7, no. 5, pp. 1588–1601, 2023.

S. I. S. Al-Hawary et al., “Multiobjective optimization of a hybrid electricity generation system based on waste energy of internal combustion engine and solar system for sustainable environment,” Chemosphere, p. 139269, 2023.

D. Apriani, V. T. Devana, A. P. Sagala, P. A. Sunarya, U. Rahardja, and E. P. Harahap, “Security using blockchain based OTP with the concept of IoT publish/subscribe,” in AIP Conference Proceedings, 2023, vol. 2808, no. 1.

T. Hariguna, B. Bin Madon, and U. Rahardja, “User intention to adopt blockchain certificate authentication technology towards education,” in AIP Conference Proceedings, 2023, vol. 2808, no. 1.

U. Rahardja, C. T. Sigalingging, P. O. H. Putra, A. Nizar Hidayanto, and K. Phusavat, “The impact of mobile payment application design and performance attributes on consumer emotions and continuance intention,” SAGE Open, vol. 13, no. 1, p. 21582440231151920, 2023.

U. Rahardja, I. D. Hapsari, P. O. H. Putra, and A. N. Hidayanto, “Technological readiness and its impact on mobile payment usage A case study of go pay,” Cogent Eng., vol. 10, no. 1, p. 2171566, 2023.

Q. Aini, D. Manongga, U. Rahardja, I. Sembiring, and A. U. Hasanah, “Scheme iLearning DApps for Education using Blockchain-Based,” in 2022 IEEE Creative Communication and Innovative Technology (ICCIT), 2022, pp. 1–7.

B. Rawat, A. S. Bist, U. Rahardja, Q. Aini, and Y. P. A. Sanjaya, “Recent deep learning based nlp techniques for chatbot development An exhaustive survey,” in 2022 10th International Conference on Cyber and IT Service Management (CITSM), 2022, pp. 1–4.

K. B. Rii, “Digital Ilearning Chain Scheme in Education Blockchain Based,” Aptisi Trans. Technopreneursh., vol. 4, no. 2, pp. 174–183, 2022.

A. Felix and G. D. Rembulan, “Analysis of Key Factors for Improved Customer Experience, Engagement, and Loyalty in the E Commerce Industry in Indonesia,” Aptisi Trans. Technopreneursh., vol. 5, no. 2sp, pp. 196–208, 2023.

M. Hardini, M. H. R. Chakim, L. Magdalena, H. Kenta, A. S. Rafika, and D. Julianingsih, “Image based Air Quality Prediction using Convolutional Neural Networks and Machine Learning,” Aptisi Trans. Technopreneursh., vol. 5, no. 1Sp, pp. 109–123, 2023.

C. Zuo et al., “Deep learning in optical metrology a review,” Light Sci. Appl., vol. 11, no. 1, p. 39, 2022.

G. Fenu, R. Galici, and M. Marras, “Experts view on challenges and needs for fairness in artificial intelligence for education,” in International Conference on Artificial Intelligence in Education, 2022, pp. 243–255.

M. M. Mariani, I. Machado, V. Magrelli, and Y. K. Dwivedi, “Artificial intelligence in innovation research A systematic review, conceptual framework, and future research directions,” Technovation, vol. 122, p. 102623, 2023.

R. Sawhney, A. Malik, S. Sharma, and V. Narayan, “A comparative assessment of artificial intelligence models used for early prediction and evaluation of chronic kidney disease,” Decis. Anal. J., vol. 6, p. 100169, 2023.

E. Koc and A. Yazici Ayyildiz, “An overview of tourism and hospitality scales Discussion and recommendations,” J. Hosp. Tour. Insights, vol. 5, no. 5, pp. 927–949, 2022.

A. Huang, Y. Chao, E. de la Mora Velasco, A. Bilgihan, and W. Wei, “When artificial intelligence meets the hospitality and tourism industry an assessment framework to inform theory and management,” J. Hosp. Tour. Insights, vol. 5, no. 5, pp. 1080–1100, 2022.

Z. Doborjeh, N. Hemmington, M. Doborjeh, and N. Kasabov, “Artificial intelligence a systematic review of methods and applications in hospitality and tourism,” Int. J. Contemp. Hosp. Manag., vol. 34, no. 3, pp. 1154–1176, 2022.

M. Knani, S. Echchakoui, and R. Ladhari, “Artificial intelligence in tourism and hospitality Bibliometric analysis and research agenda,” Int. J. Hosp. Manag., vol. 107, p. 103317, 2022.