MCDM-Based Blockchain and Artificial Intelligence Integration for Earthquake Risk Recommendation System

Authors

  • Aditya Widianto Prodi Informatika, Fakultas Teknologi Komunikasi dan Informatika, Universitas Nasional, Jakarta, Indonesia
  • Ratih Titi Komala Sari Prodi Informatika, Fakultas Teknologi Komunikasi dan Informatika, Universitas Nasional, Jakarta, Indonesia
  • Djarot Hindarto Prodi Informatika, Fakultas Teknologi Komunikasi dan Informatika, Universitas Nasional, Jakarta, Indonesia
  • Asrul Sani Magister Teknologi Informasi, Fakultas Teknologi Komunikasi dan Informatika, Universitas Nasional

DOI:

10.33395/sinkron.v9i4.15437

Keywords:

Blockchain, Artificial Intelligence, MCDM, Smart Contract, Earthquake Risk

Abstract

Indonesia is one of the countries with the highest earthquake vulnerability in the world because it is located at the meeting point of three major tectonic plates, namely Eurasia, Indo-Australia, and Pacific. The high risk of disaster requires a system that is capable of analyzing, predicting, and recommending earthquake-prone areas accurately, efficiently, and safely. This study aims to develop an earthquake risk recommendation system based on the integration of Artificial Intelligence (AI), Multi-Criteria Decision Making (MCDM), and Ethereum Blockchain. Earthquake data was obtained from Google Earth Engine (GEE) and geospatial data from the Geospatial Information Agency (BIG) and BMKG. The data is processed using AI algorithms for predictive analysis, then the MCDM methods of  TOPSIS, and ELECTRE are applied to determine the priority of earthquake-prone areas based on a combination of seismic parameters, population density, infrastructure vulnerability, and distance to active faults. The analysis results are stored in a decentralized manner using the Ethereum Blockchain through smart contracts to ensure data integrity, security, and transparency. The research results show that the integration of AI–MCDM is capable of providing earthquake risk recommendations with high accuracy, while the application of blockchain ensures that the results cannot be manipulated. This system is expected to become a decision-making tool for disaster management agencies such as BMKG and BNPB in data-based earthquake risk mitigation.

GS Cited Analysis

Downloads

Download data is not yet available.

References

AbdelAziz, N. M., mohamed, D., & Soliman, H. (2025). A Multi-Criteria Decision-Making Framework for Evaluating Emerging Digital Technologies in Supply Chain Optimization A Multi-Criteria Decision-Making Framework for Evaluating Emerging Digital Technologies in Supply Chain Optimization A Multi-Criteria Decision-Making Framework for Evaluating Emerging Digital Technologies in Supply Chain Optimization. In Neutrosophic Sets and Systems (Vol. 87).

Alemdar, K. D. (2025). Seismic risk assessment of transportation networks for the impending Istanbul earthquake with GIS-based MCDM approach. Natural Hazards, 121(9), 10085–10123. https://doi.org/10.1007/s11069-025-07199-y

Amani, M., Ghorbanian, A., Ahmadi, S. A., Kakooei, M., Moghimi, A., Mirmazloumi, S. M., Moghaddam, S. H. A., Mahdavi, S., Ghahremanloo, M., Parsian, S., Wu, Q., & Brisco, B. (2020). Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 5326–5350. https://doi.org/10.1109/JSTARS.2020.3021052

Anggraini, S., Fatihatuttizqi, M., Kepercayaan, M., Di, P., Fintech, S., & Fatihaturrizqi, M. (n.d.). Konvergensi Teknologi Blockchain dan Artificial Intelligence Untuk. https://journal.perkivi.or.id

Astarita, V., Martino, G., Guido, G., Haghshenas, S. S., & Shaffiee Haghshenas, S. (2025). Risk Management in Transportation Systems: The use of Blockchain for risk reduction in disaster’s occurrence. Procedia Computer Science, 257, 428–435. https://doi.org/10.1016/j.procs.2025.03.056

Cremen, G., & Galasso, C. (2021). A decision-making methodology for risk-informed earthquake early warning. Computer-Aided Civil and Infrastructure Engineering, 36(6), 747–761. https://doi.org/10.1111/mice.12670

Hindarto, D. (2023). Blockchain-Based Academic Identity and Transcript Management in University Enterprise Architecture. Sinkron, 8(4), 2547–2559. https://doi.org/10.33395/sinkron.v8i4.12978

Hindarto, D., Damastuti, F. A., Marzuki, I., Rachmadi, R. F., & Hariadi, M. (2025). Blockchain and MCDM Framework for Secure Geospatial Data in Landslide Risk Mitigation. International Journal of Intelligent Engineering and Systems, 18(4), 137–155. https://doi.org/10.22266/ijies2025.0531.09

Hindarto, D., & Hariadi, M. (2024). Nanotechnology Perceptions ISSN 1660-6795 www. In Nanotechnology Perceptions (Vol. 20, Issue S12). www.nano-ntp.com

Hindarto, D., Rachmadi, R. F., Hariadi, M., & Damastuti, F. A. (2025). Contextual Awareness System for Landslide Risk Recommendation in Crypto-Spatial. 2025 International Electronics Symposium (IES), 700–706. https://doi.org/10.1109/IES67184.2025.11161195

Hudi Adrian, F., & Dewayanto, T. (2024). PADA KURIKULUM AKUNTANSI: SYSTEMATIC LITERATURE REVIEW. DIPONEGORO JOURNAL OF ACCOUNTING, 13(3), 1–13. http://ejournal-s1.undip.ac.id/index.php/accounting

Javadpour, A., AliPour, F. S., Sangaiah, A. K., Zhang, W., Ja’far, F., & Singh, A. (2023). An IoE blockchain-based network knowledge management model for resilient disaster frameworks. Journal of Innovation and Knowledge, 8(3). https://doi.org/10.1016/j.jik.2023.100400

Jyothi, K., Khojaste Effatpanah, S., Ahmadi, M. H., Aungkulanon, P., Maleki, A., Sadeghzadeh, M., Sharifpur, M., & Chen, L. (2022). Comparative Analysis of Five Widely-Used Multi-Criteria Decision-Making Methods to Evaluate Clean Energy Technologies: A Case Study. https://doi.org/10.3390/su

KURNAZ, S. Ç. (2025). AI Supported Early Warning Systems in Smart Disaster Management: The Case of Kahramanmaraş Earthquakes. Pakistan Journal of Life and Social Sciences (PJLSS), 23(2). https://doi.org/10.57239/pjlss-2025-23.2.0011

Kushwaha, S. S., Joshi, S., Singh, D., Kaur, M., & Lee, H. N. (2022). Systematic Review of Security Vulnerabilities in Ethereum Blockchain Smart Contract. In IEEE Access (Vol. 10, pp. 6605–6621). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ACCESS.2021.3140091

Mae Eduardo-Igo, S., Rhodora Quiatleg, A. M., Concepcion, N. B., & Irving Jacinto, P. G. (n.d.). International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING Optimizing Disaster Management with Blockchain Technology: A Decision Support System for Disaster Risk Reduction and Management. In Original Research Paper International Journal of Intelligent Systems and Applications in Engineering IJISAE (Vol. 2025, Issue 1). www.ijisae.org

NUGROHO, H., SARI, D. K., & BAIHAQI, T. (2024). Detection Of Land Drought Using Landsat Imagery On The Google Earth Engine Platform For Forest Fire Mitigation. ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika, 12(4), 1023. https://doi.org/10.26760/elkomika.v12i4.1023

Prasetyo, A., Ridwan, T., & Voutama, A. (2024). ANALISIS SENTIMEN TERHADAP APLIKASI GBWHATSAPP MENGGUNAKAN NAIVE BAYES CLASSIFIER DAN RANDOM FOREST CLASSIFIER. JSiI (Jurnal Sistem Informasi), 11(1), 1–9. https://doi.org/10.30656/jsii.v11i1.6936

Pwavodi, J., Ibrahim, A. U., Pwavodi, P. C., Al-Turjman, F., & Mohand-Said, A. (2024). The role of artificial intelligence and IoT in prediction of earthquakes: Review. In Artificial Intelligence in Geosciences (Vol. 5). KeAi Communications Co. https://doi.org/10.1016/j.aiig.2024.100075

Raut, A., & Shevtekar, Prof. S. (2023). Fundraising Tracking System for NGOs Using Blockchain. International Journal for Research in Applied Science and Engineering Technology, 11(5), 492–496. https://doi.org/10.22214/ijraset.2023.51520

Ruan, C., Gong, S., & Chen, X. (2025). Multi-criteria group decision-making with extended ELECTRE III method and regret theory based on probabilistic interval-valued intuitionistic hesitant fuzzy information. Complex and Intelligent Systems, 11(1). https://doi.org/10.1007/s40747-024-01645-3

Taherdoost, H., & Madanchian, M. (2023). A Comprehensive Overview of the ELECTRE Method in Multi Criteria Decision-Making. Journal of Management Science & Engineering Research, 6(2), 5–16. https://doi.org/10.30564/jmser.v6i2.5637

Tashatov, N., Ospanov, R., Seitkulov, Y., Satybaldina, D., & Yergaliyeva, B. (2025). Integrating multi-criteria decision making and reinforcement learning for consensus protocol selection. Bulletin of Electrical Engineering and Informatics, 14(4), 2613–2624. https://doi.org/10.11591/eei.v14i4.9552

Downloads


Crossmark Updates

How to Cite

Widianto, A. ., Sari, R. T. K. ., Hindarto , D. ., & Sani, A. (2025). MCDM-Based Blockchain and Artificial Intelligence Integration for Earthquake Risk Recommendation System. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 9(4). https://doi.org/10.33395/sinkron.v9i4.15437

Most read articles by the same author(s)

1 2 3 4 5 > >>