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Journal : Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering)

Application of Extreme Learning Machine (ELM) for Water Level Prediction in Krueng Peusangan River Basin (2014–2023) Aznita, Meri; Rusdiana, Siti; Ramli, Ichwana; Izzaty, Atika; Ferijal, T
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 14 No. 5 (2025): October 2025
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtepl.v14i5.1638-1649

Abstract

The Krueng Peusangan Watershed in Aceh Province is highly vulnerable to flooding, with 20.39% of its area classified as flood-prone, particularly in Bireuen Regency. This study aims to develop a water level prediction model using the Extreme Learning Machine (ELM), a type of Artificial Neural Network known for its computational efficiency and ability to handle uncertainty in hydrological data. The model was trained using water level data from the Krueng Peusangan River from January 2014 to June 2023. The results show a Mean Squared Error (MSE) of 0.063, indicating high predictive accuracy. Compared to conventional methods, ELM delivers faster computation and better precision. This research contributes to the development of data-driven flood early warning systems, supports adaptive and sustainable water resource management, and offers potential for replication in other watersheds with similar characteristics. Furthermore, the model provides a scientific basis for formulating disaster risk reduction policies leveraging artificial intelligence technologies. The promising accuracy of ELM supports its potential integration into real-time flood early warning systems and long-term adaptive water resource management in vulnerable river basins.
Impact of Pyrolysis Temperature and Jatropha Seed Adhesive on the Properties of Bio-charcoal from Young Coconut Waste Anwar, Khairul; Mahidin, Mahidin; Ramli, Ichwana; Faisal, Muhammad; Sitorus, Agustami
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 13 No. 4 (2024): December 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i4.1372-1382

Abstract

This study assesses the characteristics of bio-charcoal from young coconut waste with the effect of variations in pyrolysis temperature and the addition of Jatropha seed adhesive. The physical and chemical parameters of bio- charcoal from three temperature variation treatments (380°C, 430°C, and 480°C) and three adhesive concentrations (15%, 20%, and 25%) were analyzed, including moisture content, ash content, volatile matter, calorific value and fixed carbon. In addition, the application of ANOVA and DMRT were used to evaluate the significant differences between the various treatments with significant p-value ≤ 5%. The optimal result was obtained at temperature of 430°C and 25% adhesive indicating a calorific value of 6421 cal/g, moisture content of 6.1%, ash content of 7.6% volatile matter of 7.7% and fixed carbon of 78.7%. The findings reveal that adhesive content significantly affects bio-charcoal quality, while temperature variations influence moisture content and heating value. This study concludes that optimizing temperature and adhesive concentrations can yield high-quality bio-charcoal, offering a cleaner, sustainable source. Keywords: Adhesive, DMRT, Jatropha curcas, Pyrolysis, Young coconut waste.