A Systematic Literature Review on Multi-Criteria Decision  Analysis and Machine Learning for Decision-Making in Digital  Payment Investment

Rahmat Rambe; Lukman Abdurrahman; Hanif Fakhrurroja

doi:10.24002/ijis.v9i1.13797

Authors

Rahmat Rambe Telkom University https://orcid.org/0009-0000-4662-2719
Lukman Abdurrahman Telkom University https://orcid.org/0000-0001-7288-0455
Hanif Fakhrurroja Telkom University https://orcid.org/0000-0002-2483-251X

DOI:

https://doi.org/10.24002/ijis.v9i1.13797

Abstract

The growth of financial technology has strengthened the role of digital payments in
driving the digital economy and influencing investment decision-making. This development
creates both opportunities and challenges for investors in evaluating digital payment investments.
Multi-Criteria Decision Analysis (MCDA) supports structured evaluation across multiple criteria,
while Machine Learning (ML) enhances predictive capabilities using historical and market data.
However, studies integrating MCDA and ML remain limited and unsystematic. This study
conducts a systematic literature review (SLR) based on the PRISMA framework, analyzing
publications from 2019 to 2024 related to the application of MCDA and ML in digital payment
investment and decision-making. The results indicate an increasing research trend, with commonly
applied MCDA methods such as AHP, TOPSIS, and PROMETHEE, and ML algorithms including
Support Vector Machine and Gradient Boosting. This review identifies research gaps and provides
directions for future studies and practical investment strategies in the digital payment sector.

Keywords: Digital Payment; Investment; MCDA; Machine Learning; Systematic Literature Review.

Author Biographies

Rahmat Rambe, Telkom University

Master's Student in Information Systems, Telkom University, Bandung

Lukman Abdurrahman, Telkom University

Lecturer in Information Systems at Telkom University, Bandung

Hanif Fakhrurroja, Telkom University

Lecturer in Information Systems at Telkom University, Bandung

References

[1] N. Nurchayati, R. Ariyanti, dan I. Marianingsih, “How Fintech Adoption, Digital Payment Systems, and Consumer Trust Shape Financial Performance of MSMEs,” Int. J. Bus. Law Educ., vol. 5, no. 2, hlm. 2458–2469, Okt 2024, doi: 10.56442/ijble.v5i2.895.

[2] H. U. Khan, M. Sohail, S. Nazir, T. Hussain, B. Shah, dan F. Ali, “Role of authentication factors in Fin-tech mobile transaction security,” J. Big Data, vol. 10, no. 1, hlm. 138, Sep 2023, doi: 10.1186/s40537-023-00807-3.

[3] C. T. Kawamoto, R. G. Spers, A. L. Fleury, P. R. Feldmann, dan N. D. Yoshida, “Determinants of success of mobile payments as innovations: An exploratory study based on the extant literature, the M-Pesa, Alipay, and Nubank cases, and the opinion of experts,” Future Bus. J., vol. 9, no. 1, hlm. 93, Nov 2023, doi: 10.1186/s43093-023-00272-7.

[4] S. Gupta, Y. Xie, dan H. Zafar, “Fintech and Digital Payments: Developing a Domain Knowledge Framework,” J. Inf. Syst. Educ., vol. 35, no. 2, hlm. 189–202, 2024, doi: 10.62273/HIGA9274.

[5] T. Hartono, F. Putri Oganda, dan J. Williams, “Evaluating Risk Management Strategies in Fintech and Blockchain An Empirical Approach,” APTISI Trans. Manag. ATM, vol. 9, no. 2, hlm. 210–220, Mei 2025, doi: 10.33050/atm.v9i2.2473.

[6] A. M. Shahen dan M. F. Sharaf, “The Role of Digital Payment Technologies in Promoting Financial Inclusion: A Systematic Literature Review,” FinTech, vol. 4, no. 4, hlm. 59, Okt 2025, doi: 10.3390/fintech4040059.

[7] S. Goutte, H.-V. Le, F. Liu, dan H.-J. Von Mettenheim, “Mcda strategies for portfolio optimization: a case study on Vietnamese stock market dynamics,” Ann. Oper. Res., vol. 353, no. 1, hlm. 321–351, Okt 2025, doi: 10.1007/s10479-025-06736-z.

[8] J. Černevičienė dan A. Kabašinskas, “Review of Multi-Criteria Decision-Making Methods in Finance Using Explainable Artificial Intelligence,” Front. Artif. Intell., vol. 5, hlm. 827584, Mar 2022, doi: 10.3389/frai.2022.827584.

[9] O. J. Gidiagba, L. Tartibu, dan M. Okwu, “Integrating Machine Learning with Multi-Criteria Decision-Making Models for Sustainable Supplier Selection in Dynamic Supply Chains,” Logistics, vol. 9, no. 4, hlm. 152, Okt 2025, doi: 10.3390/logistics9040152.

[10] V. P. Kumar, “Online Payment Fraud Detection Using Machine Learning,” 2024.

[11] S. K. Abbas, M. Hussain, dan Y. N. Rimal, “Machine Learning-Based Analysis of Technology Acceptance in FinTech: A Behavioral Study Using Digital Wallet Data,” SN Comput. Sci., vol. 6, no. 6, hlm. 674, Jul 2025, doi: 10.1007/s42979-025-04214-8.

[12] X. Zhang, “Machine learning insights into digital payment behaviors and fraud prediction,” Appl. Comput. Eng., vol. 77, no. 1, hlm. 203–209, Jul 2024, doi: 10.54254/2755-2721/77/2024MA0066.

[13] H. Gao dkk., “Machine learning in business and finance: a literature review and research opportunities,” Financ. Innov., vol. 10, no. 1, hlm. 86, Sep 2024, doi: 10.1186/s40854-024-00629-z.

[14] Q. Wei, W. Xiao, R. M. S. Yaqub, M. Irfan, M. Murad, dan M. Z. Yaqub, “Adoption of digital money (e-wallet) in the post COVID-19 era: The moderating role of low distribution charges and low transit time in impulsive buying: A developing country perspective,” Front. Environ. Sci., vol. 10, hlm. 984316, Jan 2023, doi: 10.3389/fenvs.2022.984316.

[15] P. Reyes-Norambuena, A. A. Pinto, J. Martínez, A. Karbassi Yazdi, dan Y. Tan, “The Application of Machine Learning and Deep Learning with a Multi-Criteria Decision Analysis for Pedestrian Modeling: A Systematic Literature Review (1999–2023),” Sustainability, vol. 17, no. 1, hlm. 41, Des 2024, doi: 10.3390/su17010041.

[16] P. Pisal dkk., “An integrated TOPSIS and ARAS method multi-criteria decision-making approach for optimizing investment portfolios using goal programming and genetic algorithm model,” Sci. Rep., vol. 15, no. 1, hlm. 34450, Okt 2025, doi: 10.1038/s41598-025-17604-y.

[17] A. Valencia-Arias dkk., “Use of machine learning in the financial sector: an analysis of trends and the research agenda,” Discov. Artif. Intell., vol. 5, no. 1, hlm. 280, Okt 2025, doi: 10.1007/s44163-025-00539-8.

[18] A. Pahsa, “Financial technology decision support systems,” J. Electr. Syst. Inf. Technol., vol. 11, no. 1, hlm. 5, Jan 2024, doi: 10.1186/s43067-023-00130-0.

[19] et al Carillo, “A systematic literature review on the use of multicriteria decision making methods for small and medium-sized enterprises,” Front. Artif. Intell., vol. 8, 2025.

[20] A. Srivastava dan P. Řežábek, “Impact of Digital Payments on the Economic growth of a country- A case of the Czech Republic,” Int. J. Econ. Sci., vol. 11, no. 1, hlm. 85–104, Apr 2022, doi: 10.52950/ES.2022.11.1.006.

[21] Q. Li dan Q. Liu, “Impact of Digital Financial Inclusion on Residents’ Income and Income Structure,” Sustainability, vol. 15, no. 3, hlm. 2196, Jan 2023, doi: 10.3390/su15032196.

[22] R. Chopra, A., K. S., “Adoption of digital transaction model by micro enterprises to target millennials in India: An exploratory study,” Soc. Bus., vol. 10(4), hlm. 411–434, 2020.

[23] C. M. Malladi, R. K. Soni, dan S. Srinivasan, “Digital financial inclusion: next frontiers—challenges and opportunities,” CSI Trans. ICT, vol. 9, no. 2, hlm. 127–134, Jun 2021, doi: 10.1007/s40012-021-00328-5.

[24] E. V. Sinelnikova-Muryleva, “Central Bank Digital Currencies: Potential Risks And Benefits,” Vopr. Ekon., hlm. 147–159, 2020.

[25] J. Calhoun, C. Minwalla, C. Helmich, F. Saqib, W. Che, dan J. Plusquellic, “Physical Unclonable Function (PUF)-Based e-Cash Transaction Protocol (PUF-Cash),” Cryptography, vol. 3, no. 3, hlm. 18, Jul 2019, doi: 10.3390/cryptography3030018.

[26] Asif, M, “Integration of Information Technology in Financial Services and its Adoption by the Financial Sector in Pakistan Title: Integration of Information Technology in Financial Services and its Adoption by the Financial Sector in Pakistan,” INVERGE J. Soc. Sci., 2022.

[27] et al Widiyanti, “OVO E-Wallet as a Platform of Digital Payment in Indonesia: An Empirical Analysis,” Monet. - J. Akunt. Dan Keuang., vol. 7(2), hlm. 237–241.

[28] Y. Indrawati, A. Wardhono, C. G. Qori’ah, dan M. Abd. Nasir, “The Impact of E-Money Diffusion on the Monetary Policy Effectiveness: Evidence from Indonesia,” dalam Proceedings of the 23rd Asian Forum of Business Education(AFBE 2019), Tanjung Benoa, Bali, Indonesia: Atlantis Press, 2020. doi: 10.2991/aebmr.k.200606.040.

[29] S. Ali, R. I. A. Khan, N. Nasir, dan M. Ghaffar, “Adoption of E-Wallet Usefulness and E-Wallet Risk in Impulsive Buying: Testing the Moderating Role of Low Distribution Charges in Post Covid-19 Era,” Pak. J. Humanit. Soc. Sci., vol. 11, no. 2, Jun 2023, doi: 10.52131/pjhss.2023.1102.0426.

[30] et al Milian, “Fintechs: A literature review and research agenda,” Electron. Commer. Res. Appl., 2019.

[31] et al Muhal, “Ensemble Approach for Credit Card Fraud Detection Using Champion-Challenger Analysis,” hlm. 1–8, 2022.

[32] et al Harshvardhan Govind, “The Evolution of Digital Payments: UPI, E-Rupee and the Future of Currency - in the Context of Urban Patna,” Int. Res. J. Adv. Eng. Manag. IRJAEM, vol. 2(3), hlm. 495–503, 2024.

[33] N. Dashkevich, S. Counsell, dan G. Destefanis, “Blockchain Application for Central Banks: A Systematic Mapping Study,” IEEE Access, vol. 8, hlm. 139918–139952, 2020, doi: 10.1109/ACCESS.2020.3012295.

[34] et al Agrawal, “A combined AHP–TOPSIS–DEMATEL approach for evaluating success factors of e-service quality: an experience from Indian banking industry,” Electron. Commer. Res., vol. 22(3), hlm. 715–747, 2022.

[35] S. Najwa, I. Haerunisa, A. E. Nabila, dan Q. Khaitsa, “Markov Chain Method to Predict The Sustainability of E-Money Use by Young People in Yogyakarta,” Bull. Islam. Econ., vol. 3, no. 2, hlm. 102–111, Des 2024, doi: 10.14421/bie.2024.032-05.

[36] A. M. Rezza, S. F. Widyana, dan A. D. Anggraeni, “Digital payment adoption: the antecedent of habit and behavioral intention,” JPPI J. Penelit. Pendidik. Indones., vol. 10, no. 4, hlm. 768–775, Des 2024, doi: 10.29210/020243563.

[37] T. Nugraha, Arifuddin, dan A. Indrijawati, “User Perceptions and the Evolution of Cashless Payment Systems: Adoption, Innovation, and Sustainability,” dalam Proceedings of the 9th International Conference on Accounting, Management, and Economics 2024 (ICAME 2024), vol. 331, M. Nohong, F. R. Cahaya, P. M. Tuan, A. Mannan, A. I. Anwar, R. R. H. Thaha, R. N. P. Nugraha, A. T. Harahap, M. T. Dharsana, dan F. I. Hermansyah, Ed., dalam Advances in Economics, Business and Management Research, vol. 331. , Dordrecht: Atlantis Press International BV, 2025, hlm. 3272–3280. doi: 10.2991/978-94-6463-758-8_274.

[38] J. McCarthy, “The regulation of RegTech and SupTech in finance: ensuring consistency in principle and in practice,” J. Financ. Regul. Compliance, vol. 31, no. 2, hlm. 186–199, Mar 2023, doi: 10.1108/JFRC-01-2022-0004.

[39] Danko, V, “Is CBDC The Remedy to Revolutionize Countries Banking &Amp; Financial Systems (With Primerely Obect to Ukraine)?,” Balt. J. Leg. Soc. Sci., hlm. 138–150, 2024.

[40] R. A. Hasanah, D. P. Ananda, N. Ramadhani, dan M. A. Ghapur, “Integrasi E-Commerce dan Fintech: Solusi Masa Depan Perdagangan Digital,” J. Ilmu Pendidik., vol. 1, no. 2, 2024.

[41] Sarwan, K., Thore, S., Satav, N., Kamble, P., & Mandal, D, “A Secure E-wallet System Using Block Chain,” Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol., hlm. 454–466, 2021.

[42] Aloun, D. M, “Commercial Applications of Electronic Currencies,” Int. J. Relig., vol. 5(10), 2024.

[43] Setiawan, M., Effendi, N., Santoso, T., Dewi, V. I., & Sapulette, M. S., “Digital financial literacy, current behavior of saving and spending and its future foresight,” Econ. Innov. New Technol., vol. 31(4), hlm. 320–338, 2022.

[44] Ariyati, I., Rosyida, S., Ramanda, K., Riyanto, V., Faizah, S., & Ridwansyah, “Optimization Of The Decision Tree Algorithm Used Particle Swarm Optimization In The Selection Of Digital Payments,” J. Phys. Conf. Ser., vol. 1641(1), 2020.

[45] Vijayan, A., Ashique, A. M., Karunattu, M. K., John, A., & Pillai, M. J., “Digital Payments: Blockchain based Security Concerns and Future,” dalam 2020 International Conference on Smart Electronics and Communication (ICOSEC), Trichy, India: IEEE, 2020.

[46] L.-Y. Tay, H.-T. Tai, dan G.-S. Tan, “Digital financial inclusion: A gateway to sustainable development,” Heliyon, vol. 8, no. 6, hlm. e09766, Jun 2022, doi: 10.1016/j.heliyon.2022.e09766.

[47] Lin, A., Peng, Y., & Wu, X., “Digital finance and investment of micro and small enterprises: Evidence from China,” China Econ. Rev., 2022.

[48] W. Wayz, “Integrating Artificial Intelligence and Machine Learning in Cybersecurity for Financial Institutions,” 27 Januari 2025, Computer Science and Mathematics. doi: 10.20944/preprints202501.2013.v1.

[49] U. Bindseil, F. Panetta, dan I. Terol, “Central Bank Digital Currency: Functional Scope, Pricing and Controls,” SSRN Electron. J., 2021, doi: 10.2139/ssrn.3975939.

[50] X.-J. Lim, P. Ngew, J.-H. Cheah, T. H. Cham, dan Y. Liu, “Go digital: can the money-gift function promote the use of e-wallet apps?,” Internet Res., vol. 32, no. 6, hlm. 1806–1831, Nov 2022, doi: 10.1108/INTR-06-2021-0406.

[51] Ahmed, M. R., Meenakshi, K., Obaidat, M. S., Amin, R., & Vijayakumar, P., “Blockchain Based Architecture and Solution for Secure Digital Payment System,” IEEE, 2021.

[52] Y. Shapoval, “Central Bank Digital Currencies: Experience Of Pilot Projects And Conclusions For The Nbu”.

[53] Z. Yuping, P. Jílková, C. Guanyu, dan D. Weisl, “New Methods of Customer Segmentation and Individual Credit Evaluation Based on Machine Learning,” dalam Proceedings of the “New Silk Road: Business Cooperation and Prospective of Economic Development” (NSRBCPED 2019), St. Petersburg, Russia; Prague, Czech Republic: Atlantis Press, 2020. doi: 10.2991/aebmr.k.200324.170.

[54] A. H. Purwantini dan F. Anisa, “Fintech Payment Adoption Among Micro-Enterprises: The Role Of Perceived Risk And Trust,” J. ASET Akunt. Ris., vol. 13, no. 2, hlm. 375–386, Des 2021, doi: 10.17509/jaset.v13i2.37212.

[55] Al-Saji, D. A., “The Role of Electronic Payment Methods in Facilitating Money Transactions in Erbil City”.

[56] Chauhan, Y., & Sharma, P, “A Systematic Literature Review of Digital Payments,” Metamorph. J. Manag. Res., hlm. 173–187.

[57] Budianita, E., Okfalisa, O., & Assiddiki, M. R, “The Prediction of E-Money Circulation: Backpropagation with Genetic Algorithm Adoption,” 2021 Int. Congr. Adv. Technol. Eng. ICOTEN, hlm. 1–6, 2021.

[58] F. Allen, X. Gu, dan J. Jagtiani, “Fintech, Cryptocurrencies, and CBDC: Financial Structural Transformation in China”.

[59] Agur, I., Ari, A., & Dell’Ariccia, G, “Designing central bank digital currencies,” J. Monet. Econ., hlm. 62–79, 2022.

[60] Agarwal, S., & Zhang, J, “FinTech, Lending and Payment Innovation: A Review,” Asia-Pac. J. Financ. Stud., vol. 49(3), hlm. 353–367, 2020.

[61] M. Najib dan F. Fahma, “Investigating the Adoption of Digital Payment System through an Extended Technology Acceptance Model: an Insight from the Indonesian Small and Medium Enterprises,” Int. J. Adv. Sci. Eng. Inf. Technol., vol. 10, no. 4, hlm. 1702–1708, Agu 2020, doi: 10.18517/ijaseit.10.4.11616.

[62] S. Carbo-Valverde, P. Cuadros-Solas, dan F. Rodríguez-Fernández, “A machine learning approach to the digitalization of bank customers: Evidence from random and causal forests,” PLOS ONE, vol. 15, no. 10, hlm. e0240362, Okt 2020, doi: 10.1371/journal.pone.0240362.

[63] Mahalakshmi, V., Kulkarni, N., Pradeep Kumar, K. V., Suresh Kumar, K., Nidhi Sree, D., & Durga, S, “The Role of implementing Artificial Intelligence and Machine Learning Technologies in the financial services Industry for creating Competitive Intelligence,” Mater. Today Proc., hlm. 2252–2255, 2022.

[64] Hafizh Fakhriza, M. & Danar Dana, R, “Optimisasi pembayaran tiket bus di Jabodetabek melalui pengelompokan transaksi digital menggunakan algoritma K-Means,” JATI J. Mhs. Tek. Inform., vol. 7(1), hlm. 313–319.

[65] K. Khanna, S. Ruhlan, D. Yadav, dan D. L. Paul, “Exploring Digital Currency Adoption in India: Insight From e-Rupee Using Technology Acceptance Model Perspective,” dalam Advances in Finance, Accounting, and Economics, M. Irfan, K. Hussainey, S. A. C. Bukhari, dan Y. Nam, Ed., IGI Global, 2024, hlm. 87–103. doi: 10.4018/979-8-3693-3282-5.ch006.

[66] G. Maski dan M. Rafqi Alfian, “Analysis of the Reciprocal Effect of Inflation and Investment and the Impact of E-money Transactions on inflation and Investment in Indonesia,” Int. J. Econ. Bus. Manag. Res., vol. 07, no. 09, hlm. 27–45, 2023, doi: 10.51505/IJEBMR.2023.7903.

[67] J. N. Sari, S. G. V. Nainggolan, dan T. Wulandari, “Financial Literacy and Perceived Ease of Use on Interest in Using E-Wallet at PT Tanjung Timberindo Industry,” vol. 2, no. 1, 2023.

[68] et al Rismawan, “Analysis of FLIP Application Adoption Using the UTAUT2 Model in the Post-Covid-19 Pandemic in Indonesia,” dalam 2023 International Conference on Digital Business and Technology Management (ICONDBTM), Lombok, Nusa Tenggara Barat, Indonesia, Indonesia: IEEE, 2023.

[69] et al Apriyanti, “Consumption and E-Wallet Use Patterns in the Millennial Generation in Denpasar City in the Context of Digital Transformation,” Int. Res. J. Econ. Manag. Stud., vol. 3, no. 6, Jun 2024, doi: 10.56472/25835238/IRJEMS-V3I6P103.

[70] Ulfah, C. F. & Suriani, S., “Digital Economy Dynamics: How E-Money, Debit Cards, Inflation, and Exchange Rates Shape Money Demand Stability in Indonesia,” Grimsa J. Bus. Econ. Stud., vol. 2(1), hlm. 39–51.

[71] K. Ahiabenu, “A Comparative Study of the Design Frameworks of the Ghanaian and Nigerian Central Banks’ Digital Currencies (CBDC)”.

[72] et al Kurnia Rahayu, “Digitalization and informal MSME: Digital financial inclusion for MSME development in the formal economy,” J. East. Eur. Cent. Asian Res. JEECAR, vol. 10(1), hlm. 9–19, 2023.

[73] Iscan, C., & Akbulut, F. P., “Fraud Detection using Recurrent Neural Networks for Digital Wallet Security,” 2023 8th Int. Conf. Comput. Sci. Eng. UBMK, hlm. 538–542, 2023.

[74] Podtserkovnyi, O., Reznik, N., Zghama, A., Tsurkanu, S., & Kovalevych, I., “Problems of Cryptocurrency Transactions: Foreign Experience and Development Prospects in Ukraine,” hlm. 847–857, 2021.

[75] H. Nabilou, “Central Bank Digital Currencies: Preliminary Legal Observations,” SSRN Electron. J., 2019, doi: 10.2139/ssrn.3329993.

[76] Q. M. H. Mumtaza, S. I. Nabillah, S. Amaliya, Y. Rosabella, dan J. A. Hammad, “Worldwide mobile wallet: a futuristic cashless system,” Bull. Soc. Inform. Theory Appl., vol. 4, no. 2, hlm. 70–75, Sep 2020, doi: 10.31763/businta.v4i2.204.

[77] J. Kumar dan Dr. S. S. Gupta, “Impact of Artificial Intelligence towards customer relationship in Indian banking industry,” Gyan Manag. J., vol. 17, no. 1, hlm. 105–115, Mar 2023, doi: 10.48165/gmj.2022.17.1.12.

[78] Iscan, C., Nardemir, M. A., & Akbulut, F. P., “A comparative analysis of fraud detection from diverse datasets to algorithmic performance,” 2023 8th Int. Conf. Comput. Sci. Eng. UBMK, hlm. 543–547, 2023.

[79] Abdullahi, M., Ahmad, A., Pandey, B. K., & Pandey, D., “Digital Currency Adoption: A Comparative Analysis of Global Trends and the Nigerian eNaira Digital Currency,” SN Comput. Sci., vol. 5(5), 2024.

[80] P. Saxena, “Navigating The Digital Frontier: Role Of Digital Financial Literacy In Shaping The E-Payment Platform’s Dynamics,” SSRN Electron. J., 2024, doi: 10.2139/ssrn.4862885.

[81] Gong, H., Thapar, H., & Thapar, A., “Central bank digital currencies: From design to issuance and distribution — A case study of China’s sovereign digital currency,” J. Digit. Bank., vol. 7(2), hlm. 166–187, 2022.

[82] Dhanaraj, S., Pitchaipillai, P., & Sivakumar, B., “The Edge: Expert Insights on Commerce, Management, and Computer Science for 2025,” 2025.

[83] Ramayanti, R., Rachmawati, N. A., Azhar, Z., & Nik Azman, N. H., “Exploring intention and actual use in digital payments: A systematic review and roadmap for future research.,” Comput. Hum. Behav. Rep., 2024.

[84] S. K. Singh, Indian Institute of Management Lucknow, Lucknow, India, S. S. Singh, Shiv Nadar University, Greater Noida, India, V. L. Singh, dan Jaipuria Institute of Management Lucknow, Lucknow, India, “Predicting Adoption of Next Generation Digital Technology Utilizing the Adoption-Diffusion Model Fit: The Case of Mobile Payments Interface in an Emerging Economy,” Access J. - Access Sci. Bus. Innov. Digit. Econ., vol. 4, no. 1, hlm. 130–148, Jan 2023, doi: 10.46656/access.2023.4.1(10).

[85] Goodell, G., Toliver, D. R., & Nakib, H. D, “A Scalable Architecture for Electronic Payments,” hlm. 645–678.

[86] S. Teker, D. Teker, dan I. Orman, “Digital Payment Systems: A Future Outlook,” Pressacademia, hlm. 1, Jul 2022, doi: 10.17261/Pressacademia.2022.1613.

[87] Mahesh, A., & Ganesh Bhat, S., “A Systematic Review and Research Agenda of Digital Payment System with reference to Unified Payment Interface,” Int. J. Manag. Technol. Soc. Sci. IJMTS, vol. 7(2), hlm. 679–709, 2022.

[88] G. P. Gusti dan H. Da, “Digital Commerce Transformation: A Study On The Impact Of E-Money, E-Wallet, And E-Commerce Use On Consumer And Financial Behavior,” Malays. E Commer. J., vol. 7, no. 1, hlm. 50–53, Jan 2023, doi: 10.26480/mecj.01.2023.50.53.

[89] Divya, P., Palanivel Rajan, D., & Selva Kumar, N, “Analysis of Machine and Deep Learning Approaches for Credit Card Fraud Detection,” hlm. 243–254, 2021.

[90] D. Adiningsih, R. Irawati, dan T. A. Putri, “Analysis of Financial Knowledge Factors, Financial Attitude and Financial Behavior Toward User Financial Technology (Fintech) Decisions At Mercu Buana University,” Indik. J. Ilm. Manaj. Dan Bisnis, vol. 6, no. 3, hlm. 48, Agu 2022, doi: 10.22441/indikator.v6i3.14105.

[91] Lahmiri, S., & Bekiros, S, “Cryptocurrency forecasting with deep learning chaotic neural networks,” Chaos Solitons Fractals, hlm. 35–40, 2019.

[92] Yu, C., Jia, N., Li, W., & Wu, R., “Digital inclusive finance and rural consumption structure – evidence from Peking University digital inclusive financial index and China household finance survey,” China Agric. Econ. Rev., vol. 14(1), hlm. 165–183, 2022.

[93] P. K. Ozili, “Central bank digital currency research around the world: a review of literature,” J. Money Laund. Control, vol. 26, no. 2, hlm. 215–226, Mar 2023, doi: 10.1108/JMLC-11-2021-0126.

[94] Lo Prete, A, “Digital and financial literacy as determinants of digital payments and personal finance,” Econ. Lett., 2022.

[95] Chatterjee, P., Das, D., & Rawat, D. B., “Digital twin for credit card fraud detection: opportunities, challenges, and fraud detection advancements,” Future Gener. Comput. Syst., hlm. 410–426, 2024.

[96] Ekramifard, A., Amintoosi, H., Seno, A. H., Dehghantanha, A., & Parizi, R. M, “A Systematic Literature Review of Integration of Blockchain and Artificial Intelligence,” hlm. 147–160.

[97] Dr. Amtul Wahab, “Impact of Artificial Intelligence on Indian Banking Sector- A Study of Banks,” Int. Res. J. Adv. Eng. Manag. IRJAEM, vol. 2, no. 05, hlm. 1261–1268, Mei 2024, doi: 10.47392/IRJAEM.2024.0171.

[98] Buksh, Z., Salahuddin, M., & Ali, A. S., “Blockchain-Based E-Wallet: A Secure and Transparent Money Management Solution,” 2023 IEEE Asia-Pac. Conf. Comput. Sci. Data Eng. CSDE, hlm. 1–6, 2023.

[99] Behera, Y. D. P., Sahoo, T. R., & Sahoo, L, “Behavioral Intention as Mediating Driver Towards Acceptability of UPI and E-wallet for Formalization of Economy,” Orissa J. Commer., vol. 44(3), 2023.

[100] Azhmy, M. F., Suyar, A. S., & Setiamy, A. A., “Digital HRM with Machine Learning Approach,” J. Penelit. Pendidik. IPA, hlm. 18–23.

[101] T. Nathiya dan K. Janaki Priya, “Analysis of Electronic Banking and Information Technology using the TOPSIS Method,” REST J. Bank. Account. Bus., vol. 2, no. 2, hlm. 32–41, Jun 2023, doi: 10.46632/jbab/2/2/4.

[102] R. A. Hapsari, M. D. S. Resmi, dan M. Safitri, “Urgent Implementation of Regulatory Technology and Supervisory Technology in the Financial Technology Industry,” Arena Huk., vol. 17, no. 1, hlm. 64–81, Apr 2024, doi: 10.21776/ub.arenahukum.2024.01701.4.

[103] A. F. Fitriani dan A. I. A. D. Torre, “Implementation of Digital Literacy Movement through The Alkapay (E-Money) Program,” Elem. Educ. J., vol. 4, no. 1, hlm. 17–24, Des 2024, doi: 10.53088/eej.v4i1.1752.

[104] V. Torkian, S. Bamdad, dan A. H. Sarfaraz, “Integrating AI and OR for investment decision-making in emerging digital lending businesses: a risk-return multi-objective optimization approach,” J. Oper. Res. Soc., hlm. 1–20, Mei 2025, doi: 10.1080/01605682.2025.2498652.

[105] R. Ai, Y. Zheng, S. Yüksel, dan H. Dinçer, “Investigating the components of fintech ecosystem for distributed energy investments with an integrated quantum spherical decision support system,” Financ. Innov., vol. 9, no. 1, hlm. 27, Jan 2023, doi: 10.1186/s40854-022-00442-6.

[106] H. Dong, R. Liu, dan A. W. Tham, “Accuracy Comparison between Five Machine Learning Algorithms for Financial Risk Evaluation,” J. Risk Financ. Manag., vol. 17, no. 2, hlm. 50, Jan 2024, doi: 10.3390/jrfm17020050.

[107] V. Avianingsih dan M. E. Firmansyah, “Optimalisasi Pengambilan Keputusan Promosi Digital dengan Pemasaran Berbasis Data Metode MCDM (Multiple Criteria Decision Making),” vol. 08, no. 2, 2025.

[108] Liang, T., & Li, S., “Utilizing time series analysis to forecast the growth of mobile payment users and its implications for the digital economy,” PLOS ONE, vol. 20(8), 2025.

[109] M. Amiri, M. Hashemi-Tabatabaei, M. Keshavarz-Ghorabaee, J. Antucheviciene, J. Šaparauskas, dan M. Keramatpanah, “Evaluation of Digital Banking Implementation Indicators and Models in the Context of Industry 4.0: A Fuzzy Group MCDM Approach,” Axioms, vol. 12, no. 6, hlm. 516, Mei 2023, doi: 10.3390/axioms12060516.

A Systematic Literature Review on Multi-Criteria Decision Analysis and Machine Learning for Decision-Making in Digital Payment Investment

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