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All Journal Jurnal Inovasi Pertambangan dan Lingkungan
Mulyanto Soerjodibroto
Mining Technic Department, Faculty of Science and Technology, UIN Jakarta
Engineering Environmental Science Materials Science & Nanotechnology

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ARTIFICIAL NEURAL NETWORK APPLICATION FOR HEAVY EQUIPMENT GAS EMISSION CONTROL ON ROCK BREAKING ACTIVITY Mulyanto Soerjodibroto; Victor Amrizal; Wishnu Prabowo
Jurnal Inovasi Pertambangan dan Lingkungan Vol 2, No 2 (2022): Jurnal Inovasi Pertambangan dan Lingkungan
Publisher : Syarif Hidayatullah State Islamic University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jipl.v2i2.29289

Abstract

Applications of artificial intelligence (AI) software in mining activities, both for equipment automation, data analysis and processing, identification of patterns and features data, upto determining solutions have been carried out by several mining companies. This is mainly due to mining activities naturally are always facing uncertainty and natural variability conditions. One of the AI applications is to control fuel consumption aimed at increasing the efficiency of fuel use, while in the same time reducing exhaust gas emissions from internal combustion engines, which are one of the causes of rising greenhouse gases (GHG).Utilization of AI in aimed to control fuel consumption in Rock Breaking activities in limestone quarry in the Sukabumi area, resulting a deviation rate of 0.17 for  fuel consumption prediction, which is fall in “ the good category”. Increasing the volume and variety of data for “machine learning” would  improve AI performance.Keywords : Artificial intelligence application,  fuel consumption, ICE gas emission control.
Co-Authors Victor Amrizal Wishnu Prabowo