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Journal of Computation Physics and Earth Science
Published by Yayasan Kita Menulis
ISSN : -     EISSN : 27762521     DOI : https://doi.org/10.63581/JoCPES
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Physics
Journal of Computation Physics and Earth Science (JoCPES) publishes cutting-edge research in computational physics and earth sciences. It offers a platform for researchers to share insights on computational methods, physical sciences, environmental science, and more. Topics include computational physics, material science, meteorology, climatology, geophysics, scientific computing, numerical analysis, earth sciences and etc. JoCPES accepts original research articles. JoCPES welcomes original research in: Computational Physics Computational Methods Physical Sciences Material Science Meteorology Climatology Geophysics Scientific Computing Numerical Analysis Data Analysis Modeling and Simulation Earth Sciences Interdisciplinary Research Environmental Science Physics Applications Physics Data Science Internet Of Things Digital Signal Processing Computer Science Artificial Intelligence Machine Learning Deep Learning
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 55 Documents
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Internet of Things Development for Flood Early Warning Monitoring System: A Review Iqbal Fariansyah Ridwan
Journal of Computation Physics and Earth Science (JoCPES) Vol 3 No 1 (2023): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63581/JoCPES.v3i1.01

Abstract

The purpose of this study is to conduct a systematic literature review. The process of writing a systematic literature review (SLR) is carried out in accordance with this framework. High rainfall during the rainy season can cause continuous rainfall and increase the volume of water that has the potential to cause flooding. Meanwhile, the community does not receive information or notification directly when this happens. To anticipate these problems, it is effective to develop a water level monitoring system as an IoT-based flood early warning tool. This paper is sourced from various publications on IoT-based flood detection systems. This study discusses the definition and selection of methods used in this study, what is the purpose of this study in developing an IoT-based flood detection system, how the results of the flood detection system that has been implemented are compared. In this paper, we present the results of the development of flood detection systems in each previous study. Therefore, the main purpose of this paper is to review research on the development of IoT-based flood detection systems.
Integrasi AI/ML pada Edge Computing untuk Prediksi Cuaca yang Lebih Akurat Raihan Ihwan, Muhammad Faiz
Journal of Computation Physics and Earth Science (JoCPES) Vol 2 No 1 (2022): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/sphgkp71

Abstract

The integration of Artificial Intelligence (AI) and Machine Learning (ML) into edge computing systems presents a promising avenue for achieving highly accurate weather predictions. By leveraging real-time data collection, processing, and analysis capabilities directly on edge devices, this paper outlines a practical framework for improving predictive accuracy. We explore the challenges, advantages, and methodologies of deploying ML models on edge devices for weather forecasting applications. This study incorporates recent advancements in edge computing and AI algorithms, supported by a case study that demonstrates real-world implementation and results.
Analisis Data Pemantauan Kualitas Udara Menggunakan Perangkat Berbasis Arduino Uno dengan Sensor MQ-135 De Sanctis, Patricia Varel
Journal of Computation Physics and Earth Science (JoCPES) Vol 2 No 1 (2022): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/8gnjq621

Abstract

Air quality is a critical factor that affects human health and the environment. Declining air quality, especially in urban areas, often results from increased pollution caused by transportation, industrial, and domestic activities. A real-time air quality monitoring system based on microcontrollers, such as the Arduino Uno, can be an economical and easily implemented solution [1]. This study aims to design and develop an air quality monitoring device using the Arduino Uno and the MQ-135 gas sensor. The MQ-135 sensor can detect various harmful gases, including carbon dioxide (CO₂), ammonia (NH₃), and sulfur dioxide (SO₂), which are common indicators of air quality. Data from the sensor are collected by the Arduino and displayed on an LCD screen, while remote access is facilitated through a mobile application [2]. This device provides real-time air quality information, helping communities reduce exposure to harmful pollutants. According to the literature, microcontroller- based monitoring systems with gas sensors like the MQ- 135 have proven effective and accurate for detecting air pollution in various environments. This study demonstrates that an Arduino-based air quality monitoring device can offer a practical solution for local air pollution monitoring.
Penerapan Teknologi Honeypot untuk Meningkatkan Keamanan Jaringan BMKG Sihombing, Ruth Archana
Journal of Computation Physics and Earth Science (JoCPES) Vol 2 No 1 (2022): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/01w9jw68

Abstract

The quick advancement of innovation has expanded the modernity of cyber dangers, requiring strong security measures to protect basic frameworks such as those overseen by the Meteorology, Climatology, and Geophysics Office (BMKG). This think about centers on the execution of honeypot innovation as a proactive defense component to upgrade BMKG's organize security. A case think about approach was conducted at Sekolah Tinggi Teknologi Adisutjipto, recreating BMKG organize situations to analyze and assess the viability of honeypots in recognizing and moderating cyberattacks. The investigate included the plan, arrangement, and testing of a honeypot framework custom fitted to imitate BMKG's arrange structure, capturing pernicious activity and recognizing assault designs. Comes about illustrated that the honeypot successfully recognized unauthorized get to endeavors, given experiences into attacker behaviors, and decreased the hazard of information breaches by redirecting malevolent on-screen characters absent from real systems. This paper concludes that executing honeypot innovation essentially upgrades arrange security by advertising real-time checking, risk investigation, and an extra layer of assurance against cyber dangers. The discoveries give a viable system for BMKG and other basic educate in receiving honeypots as portion of their cybersecurity methodologies. Future investigate seem investigate coordination honeypots with other progressed innovations, such as machine learning, to assist move forward security defenses.
Akselerometer dan Giroskop MEMs: Aplikasi dalam Sensor Seismik Elektrokimia Situngkir, Yusuf Hotdes Triwan; Irviandi, Risnu
Journal of Computation Physics and Earth Science (JoCPES) Vol 2 No 1 (2022): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/zhrzk442

Abstract

This journal is intended to provide an initial overview or introduction to an electrochemical seismic sensor device assisted with vibration detection features using a liquid resistance mass. This research introduces the first electrochemical seismic sensor that uses a liquid resistance mass (electrolyte solution) as a detecting element to convert environmental vibrations into active ion imbalances between electrodes, resulting in an electric current output. This paper will describe the use of MEMs in motion or vibration (seismic) analysis, validating the validity of concepts that have been widely fabricated, ranging from the use of conventional electrodes to earthquake detection and recording. In addition, this study discusses the operating principle, sensing mechanism, and applications of MEMS- based accelerometer and gyroscope sensors, where accelerometers measure linear acceleration and gyroscopes detect angular motion due to Coriolis acceleration. The comparative analysis shows the important role of MEMS sensors in various fields, such as shipping, aerospace, robotics and smart devices, and reveals the efficiency of MEMS-based electrochemical seismic sensors in earthquake monitoring with lower power and fabrication costs. This research opens up opportunities for the development of MEMS-based seismometers for environmental and geological monitoring applications, with recommendations for continued research for optimization of electrochemical materials and system integration to improve overall seismic response.
Perancangan Antarmuka Situs Web Teknologi Modifikasi Cuaca untuk Pemantauan Indeks Kualitas Udara di Wilayah Perkotaan Wijaya, Ade; Mutoha, Dimas Khabib
Journal of Computation Physics and Earth Science (JoCPES) Vol 2 No 2 (2022): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/db3zva62

Abstract

This heartfelt paper shares the thoughtful design and development of a website interface dedicated to supporting weather modification technologies through the vigilant monitoring of the Air Quality Index (AQI) in urban areas, especially in places burdened by high pollution levels, like Jabodetabek. The front-end website gently emphasizes visualizing vital parameters of air quality, such as particulate matter (PM2.5 and PM10), carbon dioxide (CO2), and ozone (O3) levels. By lovingly integrating this data into an accessible and user-friendly interface, the platform empowers users to monitor real-time air quality conditions with ease. The website aspires to provide essential stakeholders with crucial information for making compassionate decisions regarding weather modification efforts aimed at enhancing air quality for all. This study compassionately focuses on the front-end design, ensuring simplicity and clarity in presenting the complex environmental data that often overhelms us. Future work may tenderly include back-end integration for automated data updates and broadned functionalities, bringing even more support to this noble cause.
Analisis Pemodelan Regresi Pembelajaran Mesin untuk Estimasi Konsentrasi PM 2.5 di Jakarta: Pendekatan dan Implikasinya terhadap Kualitas Udara Deva Sudarjo, Brilliant Muhammad Al Hadid
Journal of Computation Physics and Earth Science (JoCPES) Vol 2 No 2 (2022): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/d9nr4659

Abstract

Air pollution by fine particulate matter (PM2.5) significantly impacts public health and environmental stability. As an air pollutant, PM2.5 is influenced by climate factors such as temperature, humidity, and wind patterns, all of which fluctuate due to climate change. This literature review explores the application of machine learning (ML) in predicting and analyzing PM2.5 behavior, focusing on three primary methods: Support Vector Regression (SVR), Random Forest (RF), and Neural Networks (NN). Based on 20 studies, this review compares the strengths and limitations of each method, evaluating how ML techniques address the complexity and variability of climate data in the context of PM2.5.
Memanfaatkan Teknik Machine Learning dan Deep Learning untuk Meramalkan Curah Hujan dan Cuaca: Sebuah Tinjauan Ndaumanu, Daniela Adolfina; Irviandi, Risnu
Journal of Computation Physics and Earth Science (JoCPES) Vol 2 No 2 (2022): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/kzexvv23

Abstract

Machine learning and deep learning are vital for achieving precise rainfall and weather forecasting, which is crucial for agricultural planning, managing water resources, and reducing disaster risks. This study reviews a range of literature on weather and rainfall forecasting, emphasizing deep learning techniques. Additionally, it examines the performance of various machine learning models, including Long Short-Term Memory (LSTM) networks and Support Vector Regression (SVR), in improving forecast accuracy. These methods show notable improvements in accuracy over traditional models. The study’s findings suggest that enhanced machine learning and deep learning models can significantly benefit weather forecasting, aiding in climate change adaptation efforts.
Analisis Prediksi Konsentrasi PM2.5 Berdasarkan Variabel Suhu Menggunakan Algoritma XGBoost (Studi Kasus: Kemayoran, Jakarta Pusat) Syahreza, Valiant Yuvi; Maghridlo, Aviv
Journal of Computation Physics and Earth Science (JoCPES) Vol 2 No 2 (2022): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/t6pf0b35

Abstract

Improvement in air quality in urban areas like Central Jakarta is a big challenge due to high activities of transport, industry, and dense population. This study aims to predict PM2.5 concentrations by utilising the XGBoost algorithm based on temperature data as the main variable. The data was taken from Kemayoran, Central Jakarta, with an observation time span from 01 January 2017 to 12 February 2017. XGBoost was chosen due to the non-linear and complex nature of the data. Based on the results of the test, it shows that the model performance is far from improved, characterized by a high Mean Squared Error (MSE) value and a small R² score. These performance limitations are driven by the small amount of data and the absence of other supporting variables such as air humidity, wind speed, and rainfall. The high PM2.5 concentration was contributed by the research location in Kemayoran, one of the most densely populated areas with high industrial activity and fossil-fuelled transport. This study provides evidence to support the addition of supporting variables and the extension of the observation time span to enhance model accuracy. Therefore, the XGBoost algorithm can be used as a promising solution for air quality prediction in urban cities where air pollution has reached its peak.
Tinjauan Pustaka: Solusi Keamanan Berbasis Honeypot untuk Menjaga Keamanan Data Kritis di BMKG Sihombing, Ruth Archana; Dewi, Ni Made Julia Puspa
Journal of Computation Physics and Earth Science (JoCPES) Vol 2 No 2 (2022): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/nt3vwk74

Abstract

The expanding dependence on advanced foundations by meteorological organizations like BMKG (Badan Meteorologi, Klimatologi, dan Geofisika) has increased the hazard of cyber attacks, which seem compromise basic climate and climate information frameworks. This paper investigates the execution of honeypot-based security arrangements as a proactive approach to defend BMKG's organize framework. Honeypots, outlined to draw potential aggressors, give important bits of knowledge into rising dangers and offer assistance to relieve dangers some time recently they reach center frameworks. By sending honeypots in BMKG's organize, this consider explores their viability in identifying and analyzing cyber-attacks focusing on meteorological information, which is basic for open security and national improvement arranging. The inquire about presents a comparative investigation of different honeypot arrangements and their capacity to distinguish modern dangers, such as zero-day misuses and Progressed Tireless Dangers (APTs), which posture critical dangers to BMKG's operations. Comes about illustrate that joining honeypots into BMKG's cybersecurity system upgrades risk discovery, diminishes reaction time, and reinforces in general information security. These discoveries highlight the potential for honeypot frameworks to play a key part in securing basic meteorological data, guaranteeing the unwavering quality and astuteness of climate information fundamental for calamity readiness and hazard administration.

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