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All Journal MANAJEMEN HUTAN TROPIKA Journal of Tropical Forest Management Agromet Jurnal Pengabdian Kepada Masyarakat (Indonesian Journal of Community Engagement) Sociae Polites: Majalah Ilmiah Sosial-Politik Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital International Journal of Remote Sensing and Earth Sciences (IJReSES) Jurnal Pusat Inovasi Masyarakat International Journal of Science and Mathematics Education Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Idung Risdiyanto
Staff In Geophysics And Meteorology Department, Faculty Of Math And Natural Science, Bogor Agriculture University
Aerospace Engineering Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Mathematics Social Sciences

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Improving Skills Through Training in Freshwater Fish Farming and Crystal Guava Jam Production (Bantarjaya Village, Bogor Regency, West Java) Umar, Ali; Risdiyanto, Idung; Albarkah, Anita Maharani; Aziz, Maulana; Bagaskara, Muhammad Fajar
Jurnal Pengabdian kepada Masyarakat (Indonesian Journal of Community Engagement) Vol 10, No 1 (2024): March
Publisher : Direktorat Pengabdian kepada Masyarakat Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jpkm.88148

Abstract

Fish farming is a type of fishing that involves cultivating various fish on land. Fish farming success can be influenced by site characteristics, water quality, fish suitability, and care. Crystal guava processing is a production utilization innovation. This has the potential to raise the value of crystal guava commodities, which can be consumed directly but are also processed into various derivative products. The community groups will be divided into two foster groups: the MSME group that makes crystal guava jam and the foster group that grows fish in irrigation ponds. This empowerment approach involves the creation of supporting infrastructure such as ponds in irrigation canals and the production of crystal guava jam. Then, using the t-test on the dependent mean and Principal Component Analysis, integrated training was carried out, including socializing and field practice, to quantify statistical development in abilities. As a result, the target community's understanding has increased. The target group (community) can increase their abilities in fish cultivation, the production of novel products (commodity derivatives), and marketing across various phases with the creation of supporting infrastructure.
Spatial Analysis of Aerosol Optical Depth in Western Java Indonesia Rajwa Hanan; Fithriya Yulisiasih Rohmawati; Idung Risdiyanto; Sonni Setiawan
International Journal of Science and Mathematics Education Vol. 2 No. 2 (2025): June: International Journal of Science and Mathematics Education
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijsme.v2i2.196

Abstract

Air quality in Western Java is highly dynamic and shaped by environmental changes influenced by intense human activities. Aerosols—tiny particulate matter that affects air quality, weather, and climate—can be quantified using Aerosol Optical Depth (AOD), which measures aerosol concentrations in the atmospheric column. This research uses spatial regression analysis to examine the spatial distribution of AOD from GEE’s platform (Google Earth Engine) and its relationship with rainfall and wind patterns during both the wet and dry seasons. The findings indicate that wind speed does not significantly impact AOD values, but wind direction does affect the distribution of rainfall and AOD, likely due to the monsoon system. During the wet season (December to March), high-intensity and widespread rainfall effectively cleanses the atmosphere of aerosols, leading to no significant effect on AOD (p-value > 0.05). In contrast, during the dry season, rainfall significantly influences AOD spatial patterns (p-value < 0.05). These results highlight the intricate interplay between meteorological factors and aerosol’s behavior, emphasizing the seasonal variability in their interactions.
KAJIAN PEMANFAATAN DATA ALOSPALSAR DALAM PEMETAAN KELEMBABAN TANAH Prasasti, Indah; Carolita, Ita; Ramdani, A. E.; Risdiyanto, Idung
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 9 No. 2 (2012)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v9i2.3263

Abstract

VALUASI JUMLAH AIR DI EKOSISTEM LAHAN GAMBUT DENGAN DATA LANDSAT 8 OLI/TIRS Risdiyanto, Idung; Wahid, Allan Nur
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 14 No. 1 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.2017.v14.a2592

Abstract

The water content of peatland ecosystems stored as gasses in the air and as liquid in the peat soil and vegetation. The presence of water was influential to the value of spectral radians received by satellite sensors. Objective of study were develop empirical model to be applied in the Landsat 8 satellite imagery interpretation to estimate water content of peatland ecosystem. Method consisted of field measurements and satellite data interpretation. Field activities aimed to obtain weather parameters such as radiation, air temperature, surface temperature, evapotranspiration (ET), relative humidity (RH), soil water content (KAT), and biomass for each land cover in peatland ecosystems. Field measurements results were used to validate the parameters derived from Landsat 8 satellite data. Water content in the air was assessed by the ET and RH, in the soil was assessed by soil heat flux (G) and in the vegetation by biomass. The results of the validation of the data field measurement with Landsat 8 showed only ET (r2 = 0.71), RH (r2 = 0.71), and biomass (r2 = 0.87) had a strong relationship, while between G and KAT had weak relationship. Conclusion of this study indicated Landsat 8 satellite data could be used to calculate the water content in the air and vegetation. Thus, estimating water content in the peatland ecosystem with satellite data can only be done on the surface.
ESTIMATION OF AIR TEMPERATURE USING REMOTE SENSING BASED ON THERMAL DIFFUSIVITY APPROACH M. Rokhis Khomarudin; Ahmad Bey; Idung Risdiyanto
International Journal of Remote Sensing and Earth Sciences Vol. 3 (2006)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2006.v3.a1203

Abstract

The measurement of air temperature usually used thermometer in the meteorology or climate station under Bureau of Meteorology and Geophysics. In Indonesia, there are some limitations in air temperature measurement and then they could not provide the spatial high resolution information. The measurement of air temperature is very important for analyzing the human comfort, photosynthesis, and vegetation growth which we need saome details spatial information. However, when data were sparse, the underlying assumptions about the variation among sampled points often differed and the choice of interpolation method and parameters then became critical. Often though data may be too sparse to use any of the interpolation methods, alternate ways to derive spatially representative values of air temperature need to researched. The data that could provide spatial information are remote sensing. The objective of this research is to estimate air temperature using remote sensing data (NOAA/AVHRR and LANDSAT/TM), based on thermal diffusivity approach. The steps of this research include the calibration of surface temperature, the determination of amplitude, and the estimation of air temperature. Based on this research, the best equation to calculate surface temperature from NOAA AVHRR is Ulivieri et al equation. This equation shows the higher correlation between surface temperatures from NOAA/AVHRR and the observation in the field than the other equation. Physically, this research could estimate air temperature from satellites data, but statistically, this research has not enough significancy to describe the field observation.
Co-Authors A. E. Ramdani Agung Sandi Budiman Ahmad Bey AHMAD BEY Alan Nur Wahid Albarkah, Anita Maharani Ana Turyanti Bagaskara, Muhammad Fajar Farhan Kurniawan Fithriya Yulisiasih Rohmawati Indah Prasasti Indah Prasasti, Indah Ita Carolita Ita Carolita, Ita Kusuma, Mochamad Afif Derma LILIK BUDIPRASETYO M. Rokhis Khomarudin M.Rokhis Khomarudin Maulana Aziz Melda Hazrina Nada Radilla Putra, I Ketut Gede Arta Rahmat Hidayat Rajwa Hanan Ramdani, A. E. Rohmawati, Fithriya Y Sonni Setiawan Umar, Ali Wahid, Allan Nur Wim Ikbal