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All Journal Reaktor TEKNIK IPTEK The Journal for Technology and Science Jurnal Media Gizi Indonesia (MGI) Jurnal Rekayasa Bahan Alam dan Energi Berkelanjutan JMM (Jurnal Masyarakat Mandiri) Jurnal Teknik Authentic Research of Global Fisheries Application Journal (Aurelia Journal) G-Tech : Jurnal Teknologi Terapan PELAGICUS: Jurnal IPTEK Terapan Perikanan dan Kelautan Jurnal Abdimas Kartika Wijayakusuma Jurnal Bluefin Fisheries Jurnal Rekayasa Kimia & Lingkungan
Meilya Suzan Triyastuti, Meilya Suzan
Politeknik Kelautan Dan Perikanan Bitung
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Journal : Jurnal Rekayasa Bahan Alam dan Energi Berkelanjutan

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Kinetic Analysis of Anaerobic Digestion of Rice Husk for Prediction of Methane Yield: Analisis Kinetika Pencernaan Anaerobik Sekam Padi untuk Prediksi Hasil Metana Lukhi Mulia Shitophyta; Nidha Amalia Nurillah; Evi Agustina; Siwi Purwanti; Meilya Suzan Triyastuti
Jurnal Rekayasa Bahan Alam dan Energi Berkelanjutan Vol. 7 No. 2 (2023)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.rbaet.2023.007.02.05

Abstract

A study of three kinetic models for predicting methane yield was performed. The selected models for predicting methane yield were first-order, modified Gompertz and Monod models. Anaerobic digestion of rice husk was simulated using the selected models. A comparative evaluation of the models was undertaken to determine the best-fit model. All models obtained an accuracy of predicted methane yield of over 0.9. The prediction of methane yield on rice husk has the most accurate model being the modified Gompertz with the least deviation of 7.37% and the least accurate model being the Monod model with the highest deviation of 20.39%.
Co-Authors Adi Suseno Annisa, Arianti Nuur Daniel H. Ndahawali Daniel H. Ndahawali Doharmat Purba Dolfie Djefrie Kaligis Dyah Ayu Rakhmayeni Enggar Ayu Saraswati Evi Agustina Fernando Wowiling Fidel James Ticoalu Finarianingrum, Tania Hadiono Soegeng Rahardjo Hetty Magrittha Pauline Ondang Lukhi Mulia Shitophyta M. Djaeni Maharani Nur Bela Pertiwi Mohamad Djaeni Mukhaimin, Iman Musa Karepesina Nadiem Anwar Nidha Amalia Nurillah Novie Wijaya Novita, Dewi Ayu Octaviani, Trisya Putu Teta Prihartini Aryanti Qifni Yasa' Ash Shiddiqi Rahma Ajizah Ratih Dea Larasati Siwi Purwanti Tania Finarianingrum Trisya Octaviani Tumanduk, Nova Utari, Febiani Yulianti Istiana