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Putri, Rosalinda Ellysa
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Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Journal : Simetris

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PREDIKSI KUALITAS UDARA BERDASARKAN PARAMETER CO DAN CO2 MENGGUNAKAN ARTIFICIAL NEURAL NETWORK Putri, Rosalinda Ellysa; Suprawikno, Suprawikno
SIMETRIS Vol 19 No 1 (2025): SIMETRIS
Publisher : Sekolah Tinggi Teknologi Ronggolawe Cepu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51901/simetris.v19i1.569

Abstract

This study aims to predict carbon monoxide (CO) and carbon dioxide (CO2) levels as indicators of air quality using the Artificial Neural Network (ANN) method with a 21-20-7 architecture. Data was collected over 28 days using the AQMSense device, with the first 21 days used for training and the remaining 7 days for testing. The results show that the ANN model effectively recognizes historical data patterns, indicated by a regression value close to 1. The prediction accuracy reached 89.96% for CO and 95.84% for CO2, demonstrating strong model performance. ANN proves to be an effective tool for daily air quality prediction and holds potential as a decision-support system for air pollution mitigation
Co-Authors agung setiawan Dewangga, Diaz Alegra Arif Ikhsan, Ridhotu Nur Maulana, Aditya Rahman Permadi, Arjun Ramadhany, Achmad Fajar Reziqna, Ayu Rahma Sofani, Mohammad Taufik Suprawikno . Ummara, Aulia