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All Journal PROSIDING SEMINAR NASIONAL Jurnal Penelitian Fisika dan Aplikasinya (JPFA) Berkala Fisika Indonesia : Jurnal Ilmiah Fisika, Pembelajaran dan Aplikasinya Journal of Aceh Physics Society Science and Technology Indonesia Indonesian Journal of Science and Education Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Physics: Theories and Applications Prosiding SNFA (Seminar Nasional Fisika dan Aplikasinya) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JPF : JURNAL PENDIDIKAN FISIKA Surya Abdimas Jurnal Pendidikan Fisika dan Teknologi Indonesian Journal on Learning and Advanced Education (IJOLAE) Indonesian Review of Physics (IRiP) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Pengabdian Kepada Masyarakat Patikala Jurnal Ilmiah Kampus Mengajar Journal of Novel Engineering Science and Technology Bincang Sains dan Teknologi
Azmi Khusnani
IKIP Muhammadiyah Maumere
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Journal : Journal of Novel Engineering Science and Technology

 1 
AI Big Data System to Predict Air Quality for Environmental Toxicology Monitoring Adi Jufriansah; Azmi Khusnani; Yudhiakto Pramudya; Nursina Sya’bania; Kristina Theresia Leto; Hamzarudin Hikmatiar; Sabarudin Saputra
Journal of Novel Engineering Science and Technology Vol. 2 No. 01 (2023): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v2i01.314

Abstract

Pollutants in the air have a detrimental effect on both human existence and the environment. Because it is closely linked to climate change and the effects of global warming, research on air quality is currently receiving attention from a variety of disciplines. The science of forecasting air quality has evolved over time, and the actions of different gases (hazardous elements) and other components directly affect the health of the ecosystem. This study aims to present the development of a prediction system based on artificial intelligence models using a database of air quality sensors.This study develops a prediction model using machine learning (ML) and a Decision Tree (DT) algorithm that can enable decision harmonization across different industries with high accuracy. Based on pollutant levels and the classification outcomes from each cluster's analysis, statistical forecasting findings with a model accuracy of 0.95 have been achieved. This may act as a guiding factor in the development of air quality policies that address global consequences, international rescue efforts, and the preservation of the gap in air quality index standardization.
Comparison of K-Means Algorithm and DBSCAN on Aftershock Activity in the Flores Sea: Seismic Activity 2019-2022 Anyela Aprianti; Adi Jufriansah; Pujianti Bejahida Donuata; Azmi Khusnani; John Ayuba
Journal of Novel Engineering Science and Technology Vol. 2 No. 03 (2023): Forthcoming Issue - Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v2i03.393

Abstract

This study seeks to determine whether the clustering method can be used to analyze Flores Sea earthquake activity. In this investigation, the BMKG Repo serves as the source for real earthquake vibration data collection. The stages of this research include preparing the data in CSV format and then preparing the data to eliminate useless data by identifying missing data. On the basis of the research data, it was determined that the K-Means and DBSCAN methods are used to determine the clustering method for analyzing earthquake activity. In addition, the data is depicted using a graphical Elbow method so that we can determine the number of clusters of aftershocks in the Flores Sea. The results of the visualization of aftershocks that followed earthquakes in the Flores Sea between 2019 and 2022 revealed three distinct groups of earthquake source depths: 33 to 70 kilometers, 150 to 300 kilometers, and 500 to 800 kilometers. In terms of the shilhoute index parameter, the K-Means algorithm is preferable to the DBSCAN algorithm when clustering results are used to analyze earthquake activity.
The Effect of Attenuation on Simulation of Tsunami Wave Propagation Using FDM Dian Ahdiany; Azmi Khusnani; Adi Jufriansah; Erwin Prasetyo
Journal of Novel Engineering Science and Technology Vol. 3 No. 01 (2024): Forthcoming Issue - Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v3i01.395

Abstract

This study seeks to investigate the shape of the surface of tsunami waves using the finite difference method and the effect of the damping function on the simulation of tsunami wave propagation using Matlab-based visualisation. The effect of attenuation on the propagation of tsunami waves is measured by the variation in energy. The results of the investigation indicate that tsunami waves have a transverse wave form, with waves propagating in a perpendicular direction. In the meantime, the analysis of the damping function reveals a decrease in the value of energy; this indicates that if the damping function is provided, it will have the effect of reducing the wave energy and propagation speed of tsunami waves. This modelling clearly and realistically illustrates the results of wave movement visualisation and provides insight for disaster mitigation and coastal protection.
Co-Authors Ade Anggraini Adi Jufriansah Anis Rohadatul Niehlah Anyela Aprianti Arief Hermanto Arief Hermanto Arief Hermanto Colomeischi Aurora Adina Danurdara Setiamukti Dedi Suwandi Wahab Dian Ahdiany Donuata, Pujianti Bejahida Endang Sulastri Erwin Prasetyo Fitri Nur Hikmah Hamzarudin Hikmatiar hikmatiar, hamzarudin Irfan Miftahul Fauzi Ishafit Ishafit Isma Alip John Ayuba Kartika Dewi Rahmawati Konsenius Wiran Wae Kristina Theresia Leto M Taufiqurrahman Moh. Toifur Mohammad Fitri Mohammad Fitri Mohammad Fitri Muhammad Ihsan Mulya Afriyanto Mulya Afriyanto Mulya Afriyanto Mulya Afriyanto Nurdin H. Abd. Rahman S. Nursina Sya'bania Ota Welly Jenni Thalo Ota Welly Jenni Thalo PRASETYO, ERWIN Rahmawati Husein Rizalul Fiqry Sabarudin Saputra Sabarudin Saputra Saharul Saharul Saharul Tria Puspita Sari Wahyuningsih, Wahyuningsih Yanto Yanto Yoman Ribeta Ratu Yohakim Yudhiakto Pramudya Yudhiakto Pramudya Yudhiakto Pramudya Yunita Kristianti Subandi Zulfakriza Zulfakriza