The Influence of Digital Artificial Intelligence Technology on Quality of Life with a Global Perspective

Authors

  • Sandy Kosasi STMIK Pontianak
  • Chandra Lukita University of Catur Insan Cendekia Cirebon
  • Mochamad Heru Riza Chakim University of Raharja
  • Adam Faturahman University of Raharja
  • Dhiyah Ayu Rini Kusumawardhani University of Raharja

DOI:

https://doi.org/10.34306/att.v5i3.354

Keywords:

Quality of Life, Technology AI Digital, Performance Expectancy, UTAUT, PLS-SEM

Abstract

The rapid development of digital technology and artificial intelligence (AI) has brought significant changes in many areas of life, including business, healthcare, education, and entertainment. The great potential of AI technologies to provide positive benefits to society is balanced with concerns about their negative impact on quality of life. This study aims to explore the influence of digital AI technology on the overall quality of life around the world, focusing on the Performance Expectancy, Effort Expectancy, and Use Behavior aspects of digital AI technology. This research method utilizes the UTAUT (Unified Theory of Acceptance and Use of Technology) approach and collects data quantitatively through a questionnaire covering 3 variables related to digital AI technology and its influence on quality of life. Data analysis was conducted using PLS-SEM (Partial Least Squares - Structural Equation Modeling) to identify important aspects related to the advantages and disadvantages of AI technology. The results from the 70 respondents indicated that digital AI technologies have the potential to improve quality of life by meeting performance expectations and providing ease of use, and a balanced approach is needed in the development and implementation of AI technologies to maximize their positive impact while minimizing their negative impact.

References

A. F. S. Borges, F. J. B. Laurindo, M. M. Spínola, R. F. Gonçalves, and C. A. Mattos, “The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions,” Int J Inf Manage, vol. 57, p. 102225, 2021.

S. F. S. Alhashmi, S. A. Salloum, and S. Abdallah, “Critical success factors for implementing artificial intelligence (AI) projects in Dubai Government United Arab Emirates (UAE) health sector: applying the extended technology acceptance model (TAM),” in International conference on advanced intelligent systems and informatics, Springer, 2019, pp. 393–405.

D. Lee and S. N. Yoon, “Application of artificial intelligence-based technologies in the healthcare industry: Opportunities and challenges,” Int J Environ Res Public Health, vol. 18, no. 1, p. 271, 2021.

A. Daly et al., “Artificial intelligence governance and ethics: global perspectives,” arXiv preprint arXiv:1907.03848, 2019.

C. Sriliasta and V. Meilinda, “Overview of Life Cycle Assessment of Current Emerging Technologies,” International Transactions on Artificial Intelligence, vol. 1, no. 2, pp. 175–181, 2023.

A. G. Pamungkas, A. Suharko, D. Apriani, and E. A. Nabila, “Analysis of the effect of quality, service price and satisfaction on patients and their impact on visits to exclusive dental clinics in south jakarta,” APTISI Transactions on Management (ATM), vol. 7, no. 1, pp. 9–14, 2023.

R. A. Febriyanti, T. Nurtino, M. L. Huzaifah, and D. A. R. Kusumawardhani, “Information Technology Development’s Impact On Library Services,” International Transactions on Education Technology, vol. 2, no. 1, pp. 23–29, 2023.

N. Diary, L. Perdanawati, A. M. Adiandari, and B. A. Wijaya, “Analysis Of The Effect Of Leadership And Organizational Culture On Organizational Citizenship Behavior With Job Satisfaction As An Intervening Variable At Ubud Wana Resort, Gianyar,” ADI Journal on Recent Innovation (AJRI), vol. 1, no. 2, pp. 121–129, 2020.

S. Samidi and R. Hidayat, “Desain Model Database Mutasi Siswa Dengan Menerapkan Metode Database Life Cycle,” Technomedia Journal, vol. 8, no. 2SP, pp. 221–235, 2023.

U. Rahardja, Q. Aini, D. Manongga, I. Sembiring, and Y. P. A. Sanjaya, “Enhancing Machine Learning with Low-Cost P M2. 5 Air Quality Sensor Calibration using Image Processing,” APTISI Transactions on Management, vol. 7, no. 3, pp. 201–209, 2023.

I. Farida, W. Ningsih, N. Lutfiani, Q. Aini, and E. P. Harahap, “Responsible Urban Innovation Working ith Local Authorities a Framework for Artificial Intelligence (AI),” Scientific Journal of Informatics, vol. 10, no. 2, pp. 121–126, 2023.

Q. Aini, U. Rahardja, D. Manongga, I. Sembiring, M. Hardini, and H. Agustian, “IoT-Based Indoor Air Quality Using Esp32,” in 2022 IEEE Creative Communication and Innovative Technology (ICCIT), IEEE, 2022, pp. 1–5.

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 Transactions on Technopreneurship (ATT), vol. 5, no. 2, pp. 109–117, 2023.

U. Rahardja, Q. Aini, D. Manongga, I. Sembiring, and I. D. Girinzio, “Implementation of tensor flow in air quality monitoring based on artificial intelligence,” International Journal of Artificial Intelligence Research, vol. 6, no. 1, 2023.

D. Apriani, R. Supriati, A. S. Rafika, and D. A. R. Kusumawardhani, “Rinfo Transformation Pendaftaran Pelayanan Pada Laboratorium Kesehatan,” Prosiding CORISINDO 2023, 2023.

D. Apriani, N. N. Azizah, N. Ramadhona, and D. A. R. Kusumawardhani, “Optimasi Transparansi Data dalam Rantai Pasokan melalui Integrasi Teknologi Blockchain,” Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi, vol. 2, no. 1, pp. 1–10, 2023.

A. Faturahman, R. D. Oktavyra, T. R. Widya, and T. R. Habibillah, “Observation of The Use of Renewable Energy Charging Infrastructure in Electric Vehicles,” in 2022 International Conference on Science and Technology (ICOSTECH), IEEE, 2022, pp. 1–9.

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 Transactions on Technopreneurship (ATT), vol. 5, no. 1Sp, pp. 109–123, 2023.

M. H. R. Chakim, A. Kho, N. P. L. Santoso, and H. Agustian, “Quality Factors of Intention To Use in Artificial Intelligence-Based AIKU Applications,” ADI Journal on Recent Innovation, vol. 5, no. 1, pp. 72–85, 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 Journal on Recent Innovation, vol. 5, no. 1Sp, pp. 78–86, 2023.

F. P. Oganda, M. H. R. Chakim, W. E. Septian, and E. D. Astuti, “User Involvement on Air Quality in Incubation Rooms in Banten-Indonesia,” ADI Journal on Recent Innovation, vol. 5, no. 1, pp. 86–92, 2023.

A. Manawar, C. Lukita, and L. Meria, “The Evolution of Financial Technology in Indonesia,” Startupreneur Business Digital (SABDA Journal), vol. 2, no. 2, pp. 192–206, 2023.

C. Lukita, M. H. R. Chakim, R. Supriati, N. P. L. Santoso, and M. F. Kamil, “Exploration of Perceived Use of Technology Using A Digital Business Perspective,” ADI Journal on Recent Innovation, vol. 5, no. 1Sp, pp. 87–96, 2023.

A. U. Hasanah, Y. Shino, and S. Kosasih, “The Role Of Information Technology In Improving The Competitiveness Of Small And SME Enterprises,” IAIC Transactions on Sustainable Digital Innovation (ITSDI), vol. 3, no. 2, pp. 168–174, 2022.

S. Kosasi, S. Millah, and N. P. L. Santoso, “Manajemen dalam Konsep dan Prinsip Pengelolaan Pendidikan menggunakan Komputasi Awan,” Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi, vol. 1, no. 1, pp. 38–45, 2022.

Y. Kumar, A. Koul, R. Singla, and M. F. Ijaz, “Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda,” J Ambient Intell Humaniz Comput, pp. 1–28, 2022.

A. Das and P. Rad, “Opportunities and challenges in explainable artificial intelligence (xai): A survey,” arXiv preprint arXiv:2006.11371, 2020.

M. Gajic et al., “Analysis of the impact of oral health on adolescent quality of life using standard statistical methods and artificial intelligence algorithms,” Children, vol. 8, no. 12, p. 1156, 2021.

Y. Zhang and Z. F. Ma, “Impact of the COVID-19 pandemic on mental health and quality of life among local residents in Liaoning Province, China: A cross-sectional study,” Int J Environ Res Public Health, vol. 17, no. 7, p. 2381, 2020.

A. F. S. Borges, F. J. B. Laurindo, M. M. Spínola, R. F. Gonçalves, and C. A. Mattos, “The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions,” Int J Inf Manage, vol. 57, p. 102225, 2021.

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Published

2023-10-23

How to Cite

Kosasi, S., Lukita, C., Chakim, M. H. R., Faturahman, A., & Kusumawardhani, D. A. R. (2023). The Influence of Digital Artificial Intelligence Technology on Quality of Life with a Global Perspective. Aptisi Transactions on Technopreneurship (ATT), 5(3), 240–250. https://doi.org/10.34306/att.v5i3.354

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