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All Journal Jurnal Pemberdayaan Masyarakat Indonesian Science Education Journal (ISEJ)
Rifqi Firmansyah
Universitas Negeri Surabaya, Indonesia
Agriculture, Biological Sciences & Forestry Education Social Sciences Other

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Arduino-Based Moving Average Filter Implementation for ‎Increasing Stability Measurement of Digital Temperature in ‎Climate Monitoring Systems Micro Moh Habibush Shidqi; Farid Baskoro; Rifqi Firmansyah; Lilik Anifah
ISEJ : Indonesian Science Education Journal Vol. 7 No. 2 (2026): February-May
Publisher : Yayasan Darussalam Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62159/isej.v7i2.2244

Abstract

This study evaluated the implementation of a Moving Average Filter (MAF) to improve the stability of digital temperature measurements in an Arduino-based microclimate monitoring system. Although low-cost digital sensors are widely used for real-time environmental monitoring, their readings may fluctuate because of short-term noise, electrical interference, and rapid environmental variation. This study aimed to determine whether a lightweight MAF algorithm could reduce temperature-data variability without substantially altering the overall temperature trend. A quantitative experimental design was employed using an Arduino Uno, a DHT22 digital temperature sensor, and a five-sample MAF window. Temperature data were acquired at one-second intervals under fixed sensor-position and normal environmental conditions. Raw and filtered readings were compared using descriptive statistical parameters, including mean, standard deviation, minimum value, maximum value, and data range. The results showed that the mean temperature remained comparable before and after filtering, decreasing only from 30.17 °C to 30.11 °C. However, the standard deviation decreased from 0.39 to 0.09, while the data range declined from 1.2 °C to 0.3 °C. The reduction in standard deviation indicated a 76.92% decrease in short-term measurement variability. Graphical comparisons also showed that filtered data followed a smoother pattern with fewer abrupt fluctuations than raw sensor readings. These findings indicate that the MAF can improve temperature-data stability in resource-limited embedded systems while maintaining the general environmental trend. Nevertheless, further studies should compare the method with Kalman, median, and adaptive filters under more dynamic environmental conditions and across multiple sensor types.
Mediator of Technology Competence and Solar Panel Module on Satisfaction, Motivation, and Self-Regulated Learning Farid Baskoro; Achmad Imam Agung; Fendi Achmad; Rifqi Firmansyah; Aristyawan Putra Nurdiansyah; Wahyu Sasongko Putro
Jurnal Pemberdayaan Masyarakat Vol 4, No 4 (2025)
Publisher : Yayasan Keluarga Guru Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46843/jpm.v4i4.579

Abstract

The development of digital technology requires higher vocational education, particularly in engineering, to emphasize practical competency and independent learning. This study aims to analyze active engagement as a mediator in the relationship between technological competency and practical modules on learning satisfaction, motivation, and self-regulated learning. The study used a quantitative-correlation approach with the Structural Equation Modeling–Partial Least Squares (SEM-PLS) analysis technique on 80 electrical engineering students, Surabaya State University (Unesa) who were selected using purposive sampling. The results showed that technological competence had a significant effect on active involvement (? = 0.291; p 0.01) and motivation (? = 0.276; p 0.05). The practical module has a significant effect on learning satisfaction, active engagement is the most potent factor influencing learning satisfaction, motivation, and self-regulated learning. Active engagement as a crucial mediating mechanism within the technology-enhanced learning framework is related to engagement-driven learning through collaborative projects, problem-based learning, and digital simulations. These findings are relevant to contributing to the digital transformation of vocational education and the needs of the renewable energy industry.
Co-Authors Achmad Imam Agung Aristyawan Putra Nurdiansyah Farid Baskoro Fendi Achmad Lilik Anifah Moh Habibush Shidqi Wahyu Sasongko Putro