https://journal.ubb.ac.id/promine/issue/feed 2024-06-12T06:32:11+00:00 Ir. Guskarnali, S.T., M.T. guskarnali@ubb.ac.id Open Journal Systems <hr> <div><strong>p-ISSN 2354-7316&nbsp;</strong><em>(Media Print)</em></div> <div><strong>e-ISSN 2620-7737&nbsp;</strong><em>(Media Online)</em></div> <div align="justify"><strong>PROMINE</strong> is a scientific periodical publication of Department of Mining Engineering, University of Bangka Belitung, which is published every <strong>June</strong> and <strong>December</strong> in a year which covers the fields of Exploration (Geology and Geophysics), Geotechnical / Geomechanics, Minerba Processing, Mining Environment, Reclamation and Post-Mining.&nbsp;<strong>PROMINE</strong> has become a journal accredited by the Ministry of Research, Technology and Higher Education based on Number SK 36/E/KPT/2019 about the Results of Scientific Journal Accreditation in Period VII of 2019 . Defined as an accredited scientific journal ranked 4. Accreditation is valid for 5 (five) years of Vol. 5 No.2, 2018 until Vol. 10 No.1, 2023.</div> <div><iframe style="border: 0px #ffffff none;" src="https://author.my.id/widget/statistik.php?sinta=5914&amp;gs=PRHbZF0AAAAJ&amp;sc=3&amp;link=" name="statistik" width="50%" height="265px" frameborder="0" marginwidth="0px" marginheight="0px" scrolling="no"></iframe></div> https://journal.ubb.ac.id/promine/article/view/3311 2024-06-12T06:32:11+00:00 Muchamad Kurniawan muchamad.kurniawan@itats.ac.id Yazid Fanani muchamad.kurniawan@itats.ac.id Siti Agustini muchamad.kurniawan@itats.ac.id Aldi Wachid muchamad.kurniawan@itats.ac.id

<p><em>The Mining industry in Indonesia plays a vital role as a source of state income and an integral part of the industrial progress of the nation. The majority of the mining industry in Indonesia employs open-pit mining. One of the weather factors that can be an obstacle in open-pit mining is rainfall. Therefore, this research focused on modelling data from rainfall, working hours and production outcomes. It applied the Artificial Neural Network algorithm with an input layer consisting of two neurons, a hidden layer with two neurons, and an output layer. The data on Rainfall working hours, and production results were trained to produce a model that, later on, will be used to predict the value of production results.</em> <em>For model testing, this study uses two parameters, namely learning rate and epoch. From 90 times of testing, the best model was obtained with a learning rate value of 0.3 and an epoch of 1000 which resulted in an RMSE error of 0.004838259401280330 </em></p>

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