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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Mandalika Mathematics and Educations Journal
Nisa, Alvi Khairin
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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TIME SERIES MODEL WITH LONG SHORT-TERM MEMORY EFFECT FOR GREENHOUSE GAS ESTIMATION IN INDONESIA Saputra, Ridho; Nisa, Alvi Khairin; Ramadhani, Nia; Almuhayar, Mawanda; Devianto, Dodi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp949-960

Abstract

Climate change is one of the major challenges in the world today, characterized by changes in meteorological values, such as rainfall and temperature, caused by the concentration of greenhouse gases in the atmosphere, such as CO2, N2O, and CH4. These accumulated greenhouse gases form a layer that prevents heat radiation from escaping, causing the greenhouse effect and global warming. Addressing the effects of greenhouse gas emissions requires appropriate strategies, one of which is to predict future greenhouse gas emissions for planning appropriate actions. Time series models such as the Autoregressive Integrated Moving Average (ARIMA) model are often used but have drawbacks due to their assumption of linear relationships. On the other hand, the Long Short-Term Memory (LSTM) model, introduced by Hochreiter and Schmidhuber in 1997, can learn complex and nonlinear relationships in data. This study uses LSTM to estimate greenhouse gas emissions in Indonesia based on emitting sectors, hoping to anticipate negative impacts and reduce greenhouse gas emissions. The results show that the LSTM model has good performance with an error below 20%, and it is predicted that greenhouse gas emissions will continue to increase.
Pemodelan Matematika Penentuan Komposisi Gizi Menu Makan Bergizi Gratis untuk Siswa Sekolah Dasar dengan Metode Simpleks Susila Bahri; Vino Raditio Wibowo; Nisa, Alvi Khairin; Assyfa Razaqi; Mauriska Khairunnisa; Rini Zulkarman; Ahmad Naufal Hibatullah
Mandalika Mathematics and Educations Journal Vol 7 No 4 (2025): Desember
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v7i4.10667

Abstract

To address the issue of nutritional deficiencies among Indonesian children, the government implemented a Free Nutritious Meals (MBG) program that meets 30% of the Recommended Nutrient Intake (RNI) for one meal with five food combinations determined by the Ministry of Health. Research aims to determine the composition of the five food combinations and produce the minimum cost of MBG by constructing a linear programming mathematical model. The budget rules set by the government, along with the required amount of nutrition, were calculated as constraints in the mathematical model. The model, which minimizes the objective function subject to 11 nutritional constraints and one budget constraint, as well as non-negative sign restrictions, was solved using the Simplex Method. The model solution, obtained through several iterations for each combination, was generated using AtoZmath software. The results show that the cost of each combination meets the budget rules, and the minimum cost is in combination 1. Additionally, to ensure the budget costs in combinations 2-5 comply with the budget rules, fruit is excluded from the composition of these combinations.
Co-Authors Ahmad Naufal Hibatullah Almuhayar, Mawanda Assyfa Razaqi Bahri, Susila Devianto, Dodi Mauriska Khairunnisa Ramadhani, Nia Ridho Saputra, Ridho Rini Zulkarman Vino Raditio Wibowo