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All Journal Jurnal Teknologi JOIN (Jurnal Online Informatika) Science and Technology Indonesia JOIV : International Journal on Informatics Visualization Emerging Science Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Indonesian Physical Review Jurnal Varian Journal of Robotics and Control (JRC) Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences International Journal for Applied Information Management Volksgeist: Jurnal Ilmu Hukum dan Konstitusi Maritime Park: Journal Of Maritime Technology and Socienty Bulletin of Applied Mathematics and Mathematics Education Jurnal Ilmiah Ilmu Terapan Universitas Jambi Jurnal Pemberdayaan Masyarakat Eastasouth Journal of Effective Community Services Journal of Educational Technology and Learning Creativity International Journal of Advances in Artificial Intelligence and Machine Learning Journal of Digital Market and Digital Currency Journal of Current Research in Blockchain International Journal Research on Metaverse
Dewi, Deshinta Arrova
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Aerospace Engineering Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Journal : Journal of Current Research in Blockchain

 1 
Predicting Throughput and Latency in Hyperledger Fabric Blockchains Using Random Forest Regression Dewi, Deshinta Arrova; Kurniawan, Tri Basuki
Journal of Current Research in Blockchain Vol. 2 No. 1 (2025): Regular Issue March
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jcrb.v2i1.27

Abstract

The study focuses on enhancing the performance optimization of Hyperledger Fabric blockchains through predictive modeling using Random Forest regression. It emphasizes the importance of accurately predicting two critical performance metrics—throughput (measured in transactions per second or TPS) and latency (defined as the time taken to confirm transactions). These metrics directly influence the efficiency and user experience of blockchain applications, making their accurate prediction essential for configuring blockchain networks effectively. The research leverages data collected through Hyperledger Caliper, a benchmarking tool, which provides detailed measurements of various configuration parameters, including block size, transaction arrival rate, and the number of orderer nodes. Through rigorous exploratory data analysis, the study identifies how these parameters impact throughput and latency, revealing complex interdependencies that challenge traditional optimization approaches. Using Random Forest regression, a robust ensemble learning method, the study demonstrates that the predictive model can achieve high accuracy. The performance of the model is assessed using metrics such as R-squared values, Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE), which collectively underscore its ability to offer reliable predictions across varying configurations. The results of this research provide practical insights for blockchain administrators, allowing them to configure Hyperledger Fabric settings more efficiently, thereby reducing the trial-and-error process typically involved in performance tuning. Moreover, the study's findings contribute to the broader field of blockchain performance optimization by offering a data-driven framework that bridges theoretical analysis with practical application in real-world scenarios. Looking forward, the study suggests avenues for future research, including expanding the dataset to cover more diverse blockchain platforms and configurations, incorporating real-world deployment data for validation, and exploring additional machine learning algorithms for even greater predictive accuracy. This approach highlights the critical role of data-driven methodologies in optimizing blockchain network performance and encourages further collaboration and exploration in the domain.
Co-Authors - Kurniawan, - Achsan, Harry Tursulistyono Yani Adi Suryaputra Paramita Adi Wijaya Afriyani, Sintia Agustina, Dea Ahmad Sanmorino Alde Alanda, Alde Ali Amran Almohab, Hadi Alqudah, Mashal Kasem Alqudah, Musab Kasim Andri Andri Andriani, Putu Eka Anita Desiani Armoogum, Sheeba Armoogum, Vinaye Aryananda, Rangga Laksana Asro Asro Azali, Lalu M. Panji Aziz, RZ. Abdul Azmi, Nurhafifi Binti Bappoo, Soodeshna Batumalay, Malathy Bin Abdul Hadi, Abdul Razak Budi Prasetyo Bujang, Nurul Shaira Binti Chandra, Anurag CSA Teddy Lesmana Devi Udariansyah Diana Diana Dita Amelia, Dita Efrizoni, Lusiana Elyakim Nova Supriyedi Patty, Elyakim Nova Supriyedi Endro Setyo Cahyono, Endro Setyo Eva Yulia Puspaningrum Fadly Fadly Fara Disa Durry Fatoni, Fatoni Fikri, Ruki Rizal Nul Firosha, Ardian Fitriyani, Amelia Sofa Fuad, Eyna Fahera Binti Eddie Habib, Shabana Hanan, Nur Syuhana binti Abd Hasibuan, M.S. Hasibuan, Muhammad Siad Henderi . Hendra Kurniawan Heng, Chang Ding Hidayani, Nieta Hisham, Putri Aisha Athira binti Humairah, Sayyidah I Gede Susrama Mas Diyasa Irianto, Suhendro Y. Irwansyah Irwansyah Ismail, Abdul Azim Bin Isnawijaya, Isnawijaya Jayawarsa, A.A. Ketut Junfithranaa, Anggy Pradifta Kezhilen, Motean Khasanah, Eka Uswatun Kijsomporn, Jureerat Kurniawan, Tri Basuki Lexianingrum, Siti Rahayu Pratami Lies Sulistiani Lin, Leong Chi M Said Hasibuan M. Anjar Pamungkas M. Fariz Fadillah Mardianto Maizary, Ary Malik Cahyadin Mantena, Jeevana Sujitha MARIA BINTANG Mashal Alqudah Melanie, Nicolas Misinem, Misinem Mohd Salikon, Mohd Zaki Motean, Kezhilen Muhammad Islam, Muhammad Muhammad Nasir Muhayeddin, Abdul Muniif Mohd Murnawan, Murnawan Nathan, Yogeswaran Nazmi, Che Mohd Alif Nella Sumika Putri Okengwu, Ugochi Oktavia, Fania Onn, Choo Wou Panguluri, Padmavathi Periasamy, Jeyarani Pratiwi, Ananda Pratiwi, Firda Aulia Praveen, S Phani Putra, Muhammad Daffa Arviano Putrie, Andi Vania Ghalliyah R Rizal Isnanto Rahmadani, Olivia Rendra Gustriansyah Rizky, Wahyu Rizqi, Zakka Ugih Rufi'i Saelan, Saelan Samihardjo, Rosalim Saringat, Zainuri Setiawan, Ariyono Shinta Puspasari Singh, Harprith Kaur Rajinder Sirisha, Uddagiri Slamet Riyadi Sri Astuti Iriyani Sri Karnila Sri Lestari Sugiyarto Surono, Sugiyarto Sulaiman Helmi Sulaiman, Agus Sunda Ariana, Sunda Taqwa, Dwi Muhammad Tarigan, Masmur Thinakaran, Rajermani Triloka, Joko Trinawarman, Dedi Valentina, Amara Wahyu Caesarendra Wahyu Dwi Lestari Wahyuningdiah Trisari Harsanti Putri Wei, Aik Sam Wibaselppa, Anggawidia Widyangga, Pressylia Aluisina Putri Widyaningsih , Upik Wijayanti, Dian Eka Yahya Darmawan Yeh, Ming-Lang Yorman Zakari, Mohd Zaki Zakaria, Mohd Zaki