A Machine Learning Framework for Startup Investor Matchmaking to Enhance Sustainable Innovation
Article Sidebar
-
Startup, Machine Learning, AIMEE, Sustainable Innovation, Artificial Intelligence
Abstract
Accelerating sustainable innovation is a critical mandate for emerging economies. However, the high failure rate of startups, primarily driven by inefficient founder-investor alignment and information asymmetry, remains a systemic obstacle. In Indonesia, this challenge is further exacerbated by traditional matchmaking processes that rely on social networks, often excluding high-potential Micro, Small, and Medium Enterprises (MSMEs). This study introduces and validates Artificial Intelligence Machine Learning Excellence Economy (AIMEE), a novel hybrid matchmaking framework designed to democratize access to capital and accelerate the twin transition of digitalization and sustainability. Utilizing a pilot dataset of 94 startup-investor pairs from five provinces in Java, we developed a policy-aware algorithm that integrates financial metrics with five entrepreneurial dimensions, including Sovereignty Scores based on alignment with the Sustainable Development Goals (SDGs). The framework employs a lightweight neural network optimized with SMOTE (Synthetic Minority Over-sampling Technique) to address data scarcity and class imbalance. Empirical validation shows that AIMEE achieves an F1-Score of 0.83, Recall of 0.82, and ROC-AUC of 0.89, significantly outperforming traditional Random Forest baselines by 12%. The model effectively identifies patterns of potential collaboration, overcoming the limitations of rigid networking. These findings confirm that AI-driven matchmaking can serve as a robust digital infrastructure to operationalize the Asta Cita vision and SDG 9, contributing to a more inclusive, resilient, and competitive innovation ecosystem in Indonesia.
Full text article
References
[1] V. Menshikov, O. Ruza, and A. Simakhova, “Role of startups in promoting innovations and sustainable economic growth,” European Journal of Sustainable Development, vol. 14, no. 2, pp. 26–26, 2025.
[2] K. Valaskova, M. Nagy, and D. Juracka, “Digital transformation and financial performance: an empirical analysis of strategic alignment in the digital age,” Journal of Enterprising Communities: People and Places in the Global Economy, 2025.
[3] G. Suryono and H. Fitriyah, “Optimizing marketing strategies through digital marketing on msme products in the culinary sector in tanggulangin district, sidoarjo regency,” Apollo: Journal of Tourism and Business, vol. 3, no. 2, pp. 380–391, 2025.
[4] W. Shafik, “Sdg 9: Industry, innovation, and infrastructure—smart technologies for sustainable industry,” in Factoring Technology in Global Sustainability: A Focus on the Sustainable Development Goals. Springer, 2025, pp. 305–331.
[5] M. H. R. Chakim, R. Tarmizi, B. D. A. Syahputra, R. Munajat et al., “Sustainable of supply chain through smart technology in indonesian retail msmes,” in Proceedings of the 7th Global Conference on Business, Management, and Entrepreneurship (GCBME 2022), vol. 255. Springer Nature, 2023, p. 389.
[6] A. Wijaya, “The role of law in providing decent work for citizens to support the national long-term development plan 2025-2045,” Citizen: Jurnal Ilmiah Multidisiplin Indonesia, vol. 5, no. 5, pp. 1294–1301, 2025.
[7] S. W. Dyatmika, B. Suyanto, E. Setijaningrum, A. Rizky, and T. Mkhize, “Enhancing brand loyalty through customer satisfaction strategies in digital business,” Aptisi Transactions on Technopreneurship (ATT), vol. 7, no. 2, pp. 556–566, 2025.
[8] W. Uno and F. Karim, “Regulatory strategy for utilizing augmented reality as a visual aid in science learning in rural elementary schools,” JTP-Jurnal Teknologi Pendidikan, vol. 27, no. 2, 2025.
[9] A. Agustan, D. Karmiadji, H. Soebagyo, O. B. B. Intoro, I. N. Djarot, H. Soleh, A. Irawan, and M. N. Putri, “Applying tasda framework and scenario planning for indonesian maritime research industry in 2045,” in AIP Conference Proceedings, vol. 3109, no. 1. AIP Publishing LLC, 2024, p. 030016.
[10] C. Shekhar and P. Rai, “Rising strong: How indian msmes are adapting and thriving in a post-fy2025 landscape study,” Available at SSRN 5338943, 2025.
[11] D. H. Tong, B. P. Uyen, and L. K. Ngan, “The effectiveness of blended learning on students’ academic achievement, self-study skills and learning attitudes: A quasi-experiment study in teaching the conventions for coordinates in the plane,” Heliyon, vol. 8, no. 12, 2022.
[12] K. Achuthan, S. Ramanathan, and R. Raman, “Exploring metaverse technologies in entrepreneurship through machine learning based topic modeling,” IEEE Access, 2025.
[13] O. Borges, V. Lenarduzzi, and R. Prikladnicki, “Preliminary insights to enable automation of the software development process in software startups: an investigation study from the use of artificial intelligence and machine learning,” in Proceedings of the 1st International Conference on AI Engineering: Software Engineering for AI, 2022, pp. 37–38.
[14] M. Naved, “A review of the use of machine learning and artificial intelligence in various sectors,” Available at SSRN 4397899, 2023.
[15] M. K. Benramdane, E. Kornyshova, S. Bouzefrane, and H. Maupas, “Supervised machine learning for matchmaking in digital business ecosystems and platforms,” Information Systems Frontiers, vol. 26, no. 4, pp. 1331–1343, 2024.
[16] N. Azizah, P. A. Sunarya, U. Rahardja, A. B. Mutiara, P. Prihandoko, and C. Pasha, “Improving smear-negative tuberculosis detection using data augmentation and faster r-cnn,” International Journal of Cyber and IT Service Management (IJCITSM), vol. 6, no. 1, pp. 65–77, 2026.
[17] S. Novani, C. Cyntiawati, K. Kijima, A. S. Trianto, L. Mayangsari, D. T. Alamanda, and G. Anggadwita, “Empowering digital creative ecosystem using problem structuring method and a service science perspective: A case study in cimahi and bandung, indonesia,” Asia Pacific Management Review, vol. 28, no. 2, pp. 215–228, 2023.
[18] H. Fu, H. Qi, and Y. An, “When do venture capital and startups team up? matching matters,” Pacific-Basin Finance Journal, vol. 85, p. 102361, 2024.
[19] R. Fahrudin, M. Hatta, Y. Yulianti, E. Erwin, and A. Zelene, “Machine learning for the next generation: A guide to matchmaking at startups,” IAIC Transactions on Sustainable Digital Innovation (ITSDI), vol. 6, no. 1, pp. 65–74, 2024.
[20] M. H. Nejad, “A structural model of mentorship in startup accelerators: Matching, learning, and value creation,” Univerity of Toronto Working Paper, Tech. Rep., 2024.
[21] I. U. Khan, H. Taherdoost, M. Madanchian, M. Ouaissa, S. El Hajjami, and H. Rahman, Future tech startups and innovation in the age of AI. CRC Press, 2024.
[22] C. Lukita, N. Lutfiani, A. R. S. Panjaitan, U. Rahardja, M. L. Huzaifah et al., “Harnessing the power of random forest in predicting startup partnership success,” in 2023 Eighth International Conference on Informatics and Computing (ICIC). IEEE, 2023, pp. 1–6.
[23] Y. Lin, H. Chen, W. Xia, F. Lin, Z. Wang, and Y. Liu, “A comprehensive survey on deep learning techniques in educational data mining: Y. lin et al.” Data Science and Engineering, pp. 1–27, 2025.
[24] A. O. Mulani, M. Deshmukh, V. Jadhav, K. Chaudhari, A. A. Mathew, and S. Salunkhe, “Transforming drug therapy with deep learning: The future of personalized medicine,” Drug Research, vol. 75, no. 08, pp. 326–333, 2025.
[25] A. Williams, Y. Hasudungan, and N. Azizah, “The implementation of effective financial management to increase the profitability of startups,” Startupreneur Business Digital (SABDA Journal), vol. 4, no. 1, pp. 47–54, 2025.
[26] L. Zhou, “Construction of english writing hybrid teaching model based on machine learning automatic composition scoring system,” Procedia Computer Science, vol. 208, pp. 384–390, 2022.
[27] S. Somavarapu and O. Goel, “Leveraging machine learning for a/b testing and conversion rate optimization in digital marketing.”
[28] S. Wijono, U. Rahardja, H. D. Purnomo, N. Lutfiani, and N. A. Yusuf, “Leveraging machine learning models to enhance startup collaboration and drive technopreneurship,” Aptisi Transactions on Technopreneurship (ATT), vol. 6, no. 3, pp. 432–442, 2024.
[29] 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). IEEE, 2022, pp. 1–5.
[30] L. Limajatini, S. Suhendra, G. A. Pangilinan, and M. G. Ilham, “Integration of artificial intelligence in the financial sector innovation, risks and opportunities,” International Journal of Cyber and IT Service Management, vol. 5, no. 1, pp. 58–70, 2025.
[31] D. Amiruddin, G. P. Cesna, R. Supriati, N. Lutfiani, and T. Nurtino, “Startupreneur multiproduct: Visionary ilearning on digital business,” in 2022 IEEE Creative Communication and Innovative Technology (ICCIT). IEEE, 2022, pp. 1–7.
[32] A. Pambudi, N. Lutfiani, M. Hardini, A. R. A. Zahra, and U. Rahardja, “The digital revolution of startup matchmaking: Ai and computer science synergies,” in 2023 Eighth International Conference on Informatics and Computing (ICIC). IEEE, 2023, pp. 1–6.
[33] J. Cai, A. Gaduh, and M. Sarah, “Innovative credit scoring: Unlocking financial opportunities for micro, small, and medium enterprises,” J-PAL Southeast Asia (Poverty Action Lab) Landscape Memo. J-PAL Southeast Asia. https://www. povertyactionlab. org, 2025.
[34] Y. Pasmawati, Y. N. Kunang, M. Hatta, M. H. R. Chakim, A. Rizky, F. Rahardja et al., “Augmented reality features and user experience in e-commerce using smartpls modeling,” in 2025 4th International Conference on Creative Communication and Innovative Technology (ICCIT). IEEE, 2025, pp. 1–6.
[35] M. A. Khan, J.-H. Jang, N. Iqbal, H. Jamil, S. S. A. Naqvi, S. Khan, J.-C. Kim, and D.-H. Kim, “Enhancing patient rehabilitation predictions with a hybrid anomaly detection model: Density-based clustering and interquartile range methods,” CAAI Transactions on Intelligence Technology, 2025.
[36] M. Cavus, “ggskewboxplots: Enhanced boxplots for skewed data in r,” arXiv preprint arXiv:2511.17091, 2025.
[37] M. Rodriguez, A. Rizky, Y. I. Tanjung, S. Sumliyah et al., “Optimizing e-learning platforms through adaptive learning for diverse demographics,” Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi, vol. 4, no. 1, pp. 30–39, 2025.
[38] S. Kapoor, “The role of smartpls in optimizing statistical analysis: A case study approach,” in 2025 5th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET). IEEE, 2025, pp. 1–5.
[39] L. Agusalim, “Smart pls 4 for smart facilitators: Optimizing pls-sem analysis in tkmp program,” GUYUB: Journal of Community Engagement, vol. 6, no. 2, pp. 415–438, 2025.
[40] T. Subrata, D. A. Yanto, A. Rizky, I. N. Hikam, and H. J. Situmorang, “Implementation of the tableau application to determine earthquake prone areas with geolocation features,” in 2022 IEEE Creative Communication and Innovative Technology (ICCIT). IEEE, 2022, pp. 1–6.
[41] A. E. E. Sobaih and I. A. Elshaer, “Personal traits and digital entrepreneurship: a mediation model using smartpls data analysis,” Mathematics, vol. 10, no. 21, p. 3926, 2022.
[42] K. Palanisamy and M. Muralidharan, “Predicting the matching possibility of online dating youths using novel machine learning algorithm,” Journal of Artificial Intelligence and System Modelling, vol. 2, no. 02, pp. 1–17, 2024.
[43] S. Purnama, B. L. Pradana, G. Khanna, S. Suhandi, A. Rizky, I. N. Hikam, and M. F. Kamil, “The impact of war on the cryptocurrency economy from a management perspective,” International Journal of Cyber and IT Service Management, vol. 4, no. 2, pp. 143–154, 2024.
[44] S. Malik, C. Mahanty, J. Mohanty, K. Vaghela, T. Narmadha, R. Sivaranjani, J. K. Bhutto, S. Islam, A. Khan, and A. Zewdie, “Enhancing education quality with hybrid clustering and evolutionary neural networks in a multi phase framework,” Scientific Reports, vol. 15, no. 1, p. 21323, 2025.
[45] W. Yustanti, A. I. Nurhidayat, and M. I. Java, “Optimizing tuition fee determination with k-means cluster relabeling based on centroid mapping of principal component pattern,” Journal of Information Systems Engineering and Business Intelligence, vol. 11, no. 3, pp. 445–458, 2025.
[46] M. Yusuf, M. Yusup, R. D. Pramudya, A. Y. Fauzi, and A. Rizky, “Enhancing user login efficiency via single sign-on integration in internal quality assurance system (espmi),” International Transactions on Artificial Intelligence, vol. 2, no. 2, pp. 164–172, 2024.
[47] V. H. G. Ortega, J. B. Lopez, and E. R.-V. Sanchez, “Remote laboratory based on fpga devices using the e-learning approach,” 2025.
[48] J. O. Matendechere, “Behavioral intention to use artificial intelligence among sales managers in the midwest,” Ph.D. dissertation, Grand Canyon University, 2025.
[49] R. N. Cruz and A. T. Ros´ario, “Data-driven decision-making in marketing: A systematic literature review of emerging themes and research gaps,” Systems, vol. 13, no. 12, p. 1114, 2025.
[50] Australian Government, Digital Transformation Agency, “AI in Government Policy,” https://www.digital.gov.au/ai/ai-in-government-policy, 2025, accessed: Dec. 15, 2025.
Authors
Copyright (c) 2026 Ninda Lutfiani, Mochamad Heru Riza Chakim, Sutarto Wijono, Untung Rahardja, Hindriyanto Dwi Purnomo, Agung Rizky
This work is licensed under a Creative Commons Attribution 4.0 International License.
This journal permits and encourages authors to post items submitted to the journal on personal websites while providing bibliographic details that credit its publication in this journal.
Authors are permitted to post their work online in institutional/disciplinary repositories or on their own websites. Pre-print versions posted online should include a citation and link to the final published version in Journal of Librarianship and Scholarly Communication as soon as the issue is available; post-print versions (including the final publisher's PDF) should include a citation and link to the journal's website.