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All Journal Journal of Computation Physics and Earth Science
Valiant Yuvi Syahreza
College of Meteorology Climatology and Geophysics
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Physics

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Analisis Prediksi Konsentrasi PM2.5 Berdasarkan Variabel Suhu Menggunakan Algoritma XGBoost (Studi Kasus: Kemayoran, Jakarta Pusat) Valiant Yuvi Syahreza; Aviv Maghridlo
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.
Perancangan dan Pengembangan Alat Pengukur UV dan Pelacak Surya Dual-Axis Berbasis IoT untuk Optimalisasi Pemantauan Indeks UV Secara Real-Time Dwi Agustian; Ilham Muthahhari; Valiant Yuvi Syahreza; Anton Widodo; Muchamad Rizqy Nugraha; Edward Trihadi
Journal of Computation Physics and Earth Science (JoCPES) Vol 5 No 1 (2025): 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.v5i1.01

Abstract

The ultraviolet (UV) radiation emitted by the sun has both positive and negative impacts on human life. Excessive exposure to UV rays can lead to various health issues, such as skin cancer and cataracts. Therefore, UV radiation monitoring becomes crucial, especially in the face of climate change, which may increase the intensity of UV radiation due to the depletion of the ozone layer. This study aims to design an Internet of Things (IoT)-based UV index monitoring system, equipped with a dual- axis solar tracker to optimize UV index measurements. The system utilizes the ESP32 microcontroller as the main processing unit, the UVM-30A sensor to detect UV radiation, and the DS3231 Real Time Clock (RTC) module for time synchronization. UV index data is displayed in real-time through a Liquid Crystal Display (LCD) screen and the Blynk platform for easy remote access. Test results show that the system performs well, with a low relative error compared to UV index data from the reference site uvindex.app. This system provides an innovative solution for efficient and real-time UV index monitoring, which can increase public awareness about the dangers of UV radiation.
Co-Authors Anton Widodo Aviv Maghridlo Dwi Agustian Edward Trihadi Ilham Muthahhari Muchamad Rizqy Nugraha