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All Journal Komunikasi Fisika Indonesia Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)
Ferdiansyah, Ervan
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Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Materials Science & Nanotechnology Physics

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Rancang Bangun Sistem Monitoring Gas CH4 dan CO2 Berbasis Internet of Things Studi Kasus TPST Bantar Gebang Yulianto, Moh. Hendrik; Ferdiansyah, Ervan; Wastumirad, Adi Widiatmoko
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 8 No 2 (2024): APRIL-JUNE 2024
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v8i2.1484

Abstract

The Bantar Gebang Integrated Waste Treatment Site (TPST) is one of Indonesia's largest final disposal sites. The increasing generation of waste daily can cause methane (CH4) and carbon dioxide (CO2) emissions. Methane and carbon dioxide are greenhouse gases that can cause global warminag and endanger respiratory health at specific concentrations. Therefore, the authors created an IoT-based CH4 and CO2 gas monitoring system using the ESP32 as a microcontroller, the MQ-4 sensor to measure CH4, and the MG-811 sensor to measure CO2. The tool's design is simple and portable, with a 20x4 LCD, and the Blynk website can store data via an SD card. After testing, the tool can operate properly, and the results of CH4 and CO2 gas concentrations at the Bantar Gebang TPST location are around 2.01 ppm and 419.89 ppm with regular status.
Evaluation of the Arima-Kalman model in predicting rainfall in Medan City in 2023 using observation data from 2013 – 2022 Lumbantoruan, Alva Josia; Darmawan, Yahya; Munawar, Munawar; Nardi, Nardi; Arifianto, Fendy; Ferdiansyah, Ervan
Indonesian Physics Communication Vol 22, No 1 (2025)
Publisher : Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/jkfi.22.1.15-22

Abstract

This paper aims to evaluate the ARIMA-Kalman model in predicting rainfall in Medan City for the year 2023. The data used are historical observation data of rainfall from 2013 to 2022 that have been tested for stationary and homogeneity, which proved not to require additional correction. The analysis results show that the ARIMA-Kalman model can capture the general pattern of rainfall well, and shows superiority in producing predictions that are closer to the actual data, with a mean absolute error (MAE) value of 54.11, which is lower than the MAE of the ARIMA model which reaches 55.66. Although the ARIMA model has a smaller root mean square error (RMSE) (66.67 compared to 69.75 for ARIMA-Kalman), the ARIMA-Kalman model shows better consistency, especially in capturing significant fluctuations, such as the peak rainfall that occurred in July 2023. Therefore, ARIMA-Kalman is proven to be more accurate and reliable for predicting rainfall in Medan city, making it a better choice to support water resources planning and management.
Empirical orthogonal functions (EOF) analysis of spatial patterns of dominant variability in the Indian Ocean Manik, Willy Bonanja; Darmawan, Yahya; Munawar, Munawar; Nardi, Nardi; Arifianto, Fendy; Ferdiansyah, Ervan
Indonesian Physics Communication Vol 22, No 1 (2025)
Publisher : Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/jkfi.22.1.23-26

Abstract

The Indian Ocean plays a crucial role in the global climate system, particularly in influencing the seasons in Indonesia. Sea surface temperature (SST) variability in the Indian Ocean affects rainfall patterns, extreme events, such as droughts and floods, in Indonesia. This study analyzes SST variability during the dry season (June – July – August, JJA) and rainy season (December – January – February, DJF) using satellite and reanalysis data from 1981 to 2023 with the empirical orthogonal function (EOF) method. The analysis shows that the dominant SST variability pattern during JJA is related to the Indian Ocean dipole (IOD), which influences rainfall and temperature patterns in Indonesia. In DJF, SST variability is more associated with the Asian-Australian monsoon, affecting rainfall patterns and the potential for floods. This research enhances the understanding of climate dynamics in the Indian Ocean and its impact on Indonesia, and it can be used to predict extreme climate events associated with SST variability.
Climate Suitability Analysis of Robusta Coffee and Its Projections in South Sumatera Province Whibowo, Gani Hesri; Arifianto, Fendy; Ferdiansyah, Ervan
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 13 No. 2 (2024): June 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i2.512-524

Abstract

Climate suitability will support the growth of a plant such as Robusta coffee. This study aims to analyze the suitability of the Robusta coffee plant climate and its projection in South Sumatra. Climate suitability is assessed based on the weighting of air temperature, rainfall, number of dry months, altitude, soil texture, and slopes. This study used observation data on rainfall and air temperature at 48 rain post points in the Robusta coffee farming area. The projection uses scenarios shared socioeconomic pathways (SSP) 2-4.5 and 5-8.5 of the MIROC6 model with three projection periods of 2021-2030, 2031-2040, and 2041-2050. The results showed that baseline period 35% of the area as a very suitable class and 65% in fairly suitable class. Based on the projected results of scenario SSP2-4.5 period 1 to 3 have the same percentage of area, that is 91% in very suitable class and 9% in fairly suitable class. The projected results of the scenario SSP5-8.5 show an improvement but not better than scenario SSP2-4.5. The percentage of area very suitable class for periods 1 to 3 of 89%, 50%, and 85% respectively. Keywords: Climate suitability, Projection, Robusta coffee, SSP2-4.5, SSP5-8.5.
Co-Authors Arifianto, Fendy Lumbantoruan, Alva Josia Manik, Willy Bonanja Munawar Munawar Nardi, Nardi Wastumirad, Adi Widiatmoko Whibowo, Gani Hesri Yahya Darmawan Yulianto, Moh. Hendrik