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All Journal Agromet JTSL (Jurnal Tanah dan Sumberdaya Lahan) Cakrawala Pedagogik JINAV: Journal of Information and Visualization Enthusiastic : International Journal of Applied Statistics and Data Science AB-JME: Al-Bahjah Journal of Mathematics Education Mathematical Journal of Modelling and Forecasting Journal Arunasita
Hermansah
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Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences

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DAMPAK PENGGUNAAN LAHAN TERHADAP STOK KARBON DI TANAH GAMBUT: STUDI PERBANDINGAN DAN IMPLIKASI KEBIJAKAN Ilmi, Rozatul; Hermansah; Yulnafatmawita; Yasin, Syafrimen
JTSL (Jurnal Tanah dan Sumberdaya Lahan) Vol. 13 No. 1 (2026)
Publisher : Departemen Tanah, Fakultas Bio-industri Pertanian dan Kehutanan, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jtsl.2026.013.1.1

Abstract

Tropical peatlands are among the largest carbon stocks on earth, but also the most vulnerable to anthropogenic disturbances. This study aims to analyze the impacts of land-use change on carbon stocks in peatlands, focusing on conversion to plantations, agriculture, and infrastructure, as well as to evaluate the effectiveness of restoration strategies and protection policies. Using a systematic review approach of 50 recent scientific publications (2010–2025), the results show that peatland conversion causes large amounts of carbon release, ranging from 70–120 tons of CO₂ per hectare per year, accompanied by land subsidence of up to 7 cm per year. Drainage and land fires are the main factors accelerating carbon emissions. In contrast, restoration efforts through rewetting and revegetation have been shown to reduce emissions by up to 65% and increase long-term carbon accumulation. The success of this strategy is greatly influenced by the biophysical conditions of the land, policy support, and local community participation. This study recommends the need for an integrated approach that includes moratoriums, economic incentives, legal strengthening, and technology-based monitoring as strategic steps in protecting carbon stocks and mitigating climate change.
Household Electricity Demand Forecasting in Batam from 2023 to 2047 Using Multilayer Perceptron Neural Network Ginting, Tiffani Giofanta; Hermansah; Hanggara, Yudhi
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 6 Issue 1, April 2026
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol6.iss1.art6

Abstract

The rapid growth of electricity demand in Batam, driven by increasing household and industrial consumption, necessitates accurate long-term energy forecasting. This study aimed to forecast household electricity demand in Batam from 2023 to 2047 using the multilayer perceptron (MLP) artificial neural network (ANN) model. Secondary data from PT PLN Batam (2013-2022), including customer numbers, electricity sales volume, and revenue, were analyzed. A total of 200 MLP models were trained, varying the number of hidden layers and nodes, with algorithms including BACKPROP, RPROP+, RPROP−, SAG, and SLR. The partial autocorrelation function (PACF) was used to determine the number of input layer nodes. The optimal model, using the smallest learning rate (SLR) algorithm with four hidden layers and ten nodes, achieved the best performance with the lowest mean squared error (MSE) of 35.93 and mean absolute percentage error (MAPE) of 0.47%. The projection results show a consistent increase in electricity demand, with a peak forecast of 2,114 GWh by 2047. These findings provide valuable insights for long-term energy planning and policy-making, ensuring adequate electricity supply and infrastructure development in Batam.  
Co-Authors Canas Rodrigues, Paulo Dedi Rosadi Enita, Enita fadillah, indah Ginting, Tiffani Giofanta Gusnidar Ila Rosmilawati Ilmi, Rozatul Lukman Nul Hakim Muhammad Aknil Sefano Muhammad Muhajir, Muhammad Nurhajati Hakim Oktania, Sella Pepi Novianti Rahmi, Hafiza Saputra, Rizky Armei Sara Serlina Aulia Syafrimen Yasin Teguh Budi Prasetyo Yudhi Hanggara Yulianti, Via Yulnafatmawita