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

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Analisis Perbandingan Model Regresi Linier dan XGBoost untuk Mengkaji Dampak ENSO terhadap Curah Hujan di Kota Ternate Tahun 2023 Firman Almaliky Gapri Amra; Anton Widodo; Muchamad Rizqy Nugraha
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.v5i1.02

Abstract

The purpose of this study is to evaluate how well two prediction models—linear regression and XGBoost—perform in assessing how ENSO (El Niño-Southern Oscillation) affects rainfall in Ternate City in 2023. The Meteorology, Climatology, and Geophysics Agency (BMKG) provided monthly rainfall data, while the Bureau of Meteorology (BOM) in Australia provided ENSO index data. Performance indicators such Pearson correlation analysis, the coefficient of determination (R-squared), and mean squared error (MSE) were used in the evaluation. According to the findings, the two models perform differently when it comes to capturing the pattern of the link between rainfall and ENSO; XGBoost is more adaptable but has a tendency to overfit on small amounts of data, whereas linear regression obtains a better R-squared value.
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 Dwi Agustian Edward Trihadi Firman Almaliky Gapri Amra Ilham Muthahhari Muchamad Rizqy Nugraha Valiant Yuvi Syahreza