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Comparative Validation of NASA POWER and ERA5 Satellite-Based Meteorological Data Using BMKG Observations in Bandar Lampung, Indonesia Ayu Aprilia; Alka Budi Wahidin; Ahmad Faruq Abdurrahman; Surya Prihanto; Yusril Al-Fath
Jurnal Info Sains : Informatika dan Sains Vol. 15 No. 02 (2025): Info sains, Desember 2025
Publisher : SEAN Institute

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Abstract

This study aims to evaluate the performance of satellite reanalysis data from NASA POWER and Copernicus ERA5. BMKG data was used as a reference to compare the accuracy of satellite reanalysis data. Data was specifically collected from Lampung Province for the years 2022 to 2024. The data compared includes temperature, humidity, wind speed, and rainfall. The temperature data from ERA5 provided consistent and accurate results with a MAE of 1.82 and an r of 0.59. POWER showed commendable performance in capturing relative humidity with a MAE of 5.05% and an r of 0.33. For the wind speed variable, both models showed underestimation for Copernicus and overestimation for NASA POWER. For rainfall (RR), both models failed to predict extreme weather. NASA POWER showed an MAE of 8.59 mm/day and Copernicus showed a value of 7.68 mm/day for the rainfall variable. Future research can focus on bias correction results and machine learning to overcome the challenges faced by satellite data in predicting rainfall.
From Sensors to Robots: Learning Instrumentation Physics Technology and Computer Vision for Students of SMA IT Daarul ‘Ilmi Bandar Lampung Surya Prihanto; Yusril Al Fath; Ayu Aprilia; Ahmad Faruq Abdurrahman; Raihan Rafii; Dafa Ariwinadi; Satrio; Muhammad Ajie Wahyudi
Society : Jurnal Pengabdian Masyarakat Vol. 5 No. 3 (2026): Mei
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/2ehn9487

Abstract

This community service activity was motivated by students’ limited understanding of instrumentation physics and the lack of exposure to the application of technologies such as sensors, microcontrollers, and computer vision in both daily life and industry, including related study prospects. This activity aims to enhance students’ understanding and interest in instrumentation physics through socialization and technology-based demonstrations. The implementation methods included pre-tests and post-tests to measure improvements in students’ understanding, material delivery sessions, and demonstrations of various technologies, such as sensor-based water quality monitoring systems, microcontroller-based automatic door systems, a 4-DOF robotic arm, and a Python-based computer vision system for hand detection.The results showed an improvement in students’ understanding, as indicated by an increase in the average pre-test score (x = 2.63) to the post-test score (x' = 3.31), with a mean gain of (Δx = 0.68). In addition, students’ interest in pursuing further studies in instrumentation physics also increased after the activity.Overall, this activity proved to be effective in providing students with interactive, contextual, and application-oriented learning experiences.