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All Journal Jurnal Sains dan Teknologi Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Proceedings ACES (Annual Civil Engineering Seminar) Jurnal Teknik Journal of Geoscience, Engineering, Environment, and Technology Jurnal Sinergitas PkM & CSR JURNAL SAINTIS Jurnal Ilmiah Rekayasa Sipil Unri Conference Series: Community Engagement Journal of Applied Materials and Technology Jurnal SENDI Lowland Technology International Bhakti Nagori (Jurnal Pengabdian kepada Masyarakat) SAINSTEK Jurnal Teknologi & Rekayasa Sipil
Bambang Sujatmoko
Universitas Riau
Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Physics Public Health Social Sciences Transportation

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Journal : Journal of Applied Materials and Technology

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A Comparative Study of Data-Driven Models for Discharge Forecasting: a Study Case of Siak River, Pekanbaru Water Gauge Station Fauzi, Manyuk; Sujatmoko, Bambang; Darmawan, Igeny Dwiana; Siswanto, Siswanto; Ermiyati, Ermiyati; Misriyani, Merley
Journal of Applied Materials and Technology Vol. 6 No. 2 (2025): March 2025
Publisher : AMTS and Faculty of Engineering - Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/Jamt.6.2.47-57

Abstract

The availability of long-term river discharge data covering at least 30 years is needed for proper hydrological studies, so the ability to predict river discharge is a matter of concern in the field of civil engineering. The Siak River in Pekanbaru City experiences overflowing water during the rainy season. One of the steps to prevent flooding on the Siak River is to utilize river discharge information, data-driven models utilize historical data to train or derive useful insights for predicting outputs, some data-driven models that are suitable for generating monthly historical data into new data include the Autoregressive Integrated Moving Average (ARIMA) method and the Thomas-Fiering method. The research begins by conducting the Rescaled Adjusted Partial Sums (RAPS) test to test the homogeneity of the data, then the prediction of discharge data with several schemes using the ARIMA and Thomas-Fiering methods, then the performance comparison between the two models is carried out using MAPE, RMSE, Nash-Sutcliffe, and correlation coefficient r. From the research results, it was found that the Thomas-Fiering method tends to be more accurate for predicting 1-year monthly discharge as well as long-term discharge, namely periods of 3, 5, and 7 years, with the best prediction being 1-year discharge prediction using 5 years of observed discharge with MAPE, RMSE, Nash-Sutcliffe, and correlation coefficient r values of 7.42%, 26.76 m3s-1, 0.92, and 0.96, respectively. This study could be a valuable reference for future studies in selection and further modification of data driven discharge simulation models.
Co-Authors ', Rinaldi AA Sudharmawan, AA Aisah kurnia utami amad, Ali Aminaton Marto Andika Satria Agus Andy Hendri, MT, Andy Anggraini Lenry Rahman Ari Sandhyavitri Bochari - Buchori Buchori Bunga Rabby Zalfi Citra Dewi Simbolon Darmawan, Igeny Dwiana Dedi Lesmana, Dedi Devita, Venni Doli Ananta Putra Elianora - Elsa Rina S Ermiyati Ermiyati, Ermiyati Fatharani, Aghnia Fauzi, Manyuk Ferdina, Muthia Ferry Virgiawan Firdaus Firdaus Freester, Joy Garsia, Dafit Ghofirin, Khoirul Ghofirin, Khoirul Gopal Adya Ariska Hadthya, Reinhart ' Hafiz Catur Anggoro Haji Gussafri Hendra Mulyadi Muslim Hugo Pratama Imam Suprayogi Irpan, Apdani Isdianto Isdianto Ismeddyanto, Ismeddiyanto Joleha, Joleha Khairullah, M Khoirul Ghofirin Lita Darmayanti M Fadhil Nur M Rizal Zarkani M. Rizki E. Janrosl Malik Habibillah Mardani Sebayang Mathias Robianto Mega Putri Komalasari Meiki Prayudi Mintio, Reygi Raica Misriyani, Merley Mohd Syarwan Mudjiatko Mudjiatko Mudjiatko, Mudjiatko Muhamad Yusa Muhammad Hadi Hasibuan Muhammad Khalilullah Muhammad Sukri Muhardi Nerrissa Arfiana Ongko, Andarsin Pratama, Rizki Putra, Jasman Adi Putri, Jeffilianti Tri Raeni Evanta Br. Tarigan Rahmad Sandi Rakhmad Ramadhan Randa Kurniawan Rellyadi Saputra Laset Reza Ahmad Fadhli Reza Ahmad Fadhli, Reza Ahmad Riandi, Daly Rianty Sihaloho Rinaldi Rinaldi Rinaldi Rinaldi Ririn Rindayani Robby Aulia Syuhada Rohman Rosyid S Siswanto Soewignjo Agus Nugroho Sovia Revina Sri Djuniati Suprasman Suprasman Sutikno, Sigit Sutopo Sutopo Syamsul Arifin Syarifah Sophia Vinka Zafani Vito Charly Vivi Widia Zahra Wahyudi, Rioza Wendi Nofriandi Yenita Morena Yohanna Lilis H Yudha Andestian Yudha Andestian, Yudha Zahra, Vivi Widia Zahri, Rifqi Zikron Hirvan