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All Journal Jurnal Budaya Nusantara Jurnal Pengabdian Magister Pendidikan IPA SCIENTIA JOURNAL JURNAL ILMU KEOLAHRAGAAN Journal Sport Science Indonesia (JASSI) Jurnal Ilmiah STOK Bina Guna Medan Indonesian Journal of Sport Management JRIIN :Jurnal Riset Informatika dan Inovasi Environmental and Materials International Journal of Sustainable Competitiveness on Tourism Jurnal Pengabdian Kepada Masyarakat Meambo Jayabama: Jurnal Peminat Olahraga Journal of Fisheries & Marine Jurnal Edukasi Citra Olahraga The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Supriatna
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Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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SPATIAL ANALYSIS OF QUANTITATIVE PRECIPITATION FORECAST ACCURACY BASED ON STRUCTURE AMPLITUDE LOCATION (SAL) TECHNIQUE Abdullah Ali; Achmad Rifani; Supriatna; Yunus Subagyo Swarinoto; Umi Sa’adah
International Journal of Remote Sensing and Earth Sciences Vol. 20 No. 2 (2023)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2023.v20.a3854

Abstract

Quantitative Precipitation Forecast (QPF) is the final product of a short-term forecasting algorithm (nowcasting) based on weather radar data which is widely used in hydrometeorological aspects. The calculation of the accuracy value using point data on a rainfall gauge often causes a double penalty problem because the QPF prediction results are in the form of spatial objects. This study aims to apply object-based spatial verification in analyzing the accuracy of QPF based on the Short Term Ensemble Prediction System (STEPS) algorithm using the SAL technique. The verification process is carried out by calculating the index value of the structure component (S), amplitude (A), and location (L) in the QPF prediction results based on the results of weather radar observations. The index values for components S and A have a range of -2 to 2, and 0 to 1 for component L with a perfect value of 0. The case study used is the occurrence of heavy rains that caused flooding in Bogor Regency in 2020. SAL verification results from 26 case studies used shows the average value of the components S, A, and L, respectively 0.51, 0.38, and 0.21. As many as 75% of all case studies have S and L component values less than 0.5 which indicate the structure and location of the QPF prediction object is close to the structure and location of the object of observation. A positive value in component A indicates that the QPF prediction results based on the STEPS algorithm tend to be overestimated but on a low scale, namely 0.38 out of 2.
RADAR-BASED STOCHASTIC PRECIPITATION NOWCASTING USING THE SHORT-TERM ENSEMBLE PREDICTION SYSTEM (STEPS) (CASE STUDY: PANGKALAN BUN WEATHER RADAR) Abdullah Ali; Supriatna; Umi Sa’adah
International Journal of Remote Sensing and Earth Sciences Vol. 18 No. 1 (2021)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2021.v18.a3527

Abstract

Nowcasting, or the short-term forecasting of precipitation, is urgently needed to support the mitigation circle in hydrometeorological disasters. Pangkalan Bun weather radar is single-polarization radar with a 200 km maximum range and which runs 10 elevation angles in 10 minutes with a 250 meters spatial resolution. There is no terrain blocking around the covered area. The Short-Term Ensemble Prediction System (STEPS) is one of many algorithms that is used to generate precipitation nowcasting, and is already in operational use. STEPS has the advantage of producing ensemble nowcasts, by which nowcast uncertainties can be statistically quantified. This research aims to apply STEPS to generate stochastic nowcasting in Pangkalan Bun weather radar and to analyze its advantages and weaknesses. Accuracy is measured by counting the possibility of detection and false alarms under the 5 dBZ threshold and plotting them in a relative operating characteristic (ROC) curve. The observed frequency and forecast probability is represented by a reliability diagram to evaluate nowcast reliability and sharpness. Qualitative analysis of the results showed that the STEPS ensemble produces smoothed reflectivity fields that cannot capture extreme values in an observed quasi-linear convective system (QLCS), but that the algorithm achieves good accuracy under the threshold used, up to 40 minutes lead time. The ROC shows a curved upper left-hand corner, and the reliability diagram is an almost perfect nowcast diagonal line.
COMPARISON OF THE RADIOMETRIC CORRECTION LANDSAT-8 IMAGE BASED ON OBJECT SPECTRAL RESPONSE AND VEGETATION INDEX Fadila Muchsin; Supriatna; Adhi Harmoko; Indah Prasasti; Mulia Inda Rahayu; Liana Fibriawati; Kuncoro Adi Pradhono
International Journal of Remote Sensing and Earth Sciences Vol. 18 No. 2 (2021)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2021.v18.a3632

Abstract

Landsat-8 standard level (level 1T) data received by users still in digital form can be used directly for land cover/land use mapping. These data have low radiometric accuracy when used to produce information such as vegetation indices, biomass, and land cover/land use classification. In this study, radiometric/atmospheric correction was conducted using FLAASH, 6S, DOS, TOA+BRDF and TOA method to eliminate atmospheric disturbances and compare the results with field measurements based on object spectral response and NDVI values. The results of the spectral measurements of objects in paddy fields at harvest time in the Cirebon Regency, West Java, Indonesia show that the FLAASH and 6S method have spectral responses that are close to those of objects in the field compared to the DOS, TOA and TOA+BRDF methods. For the NDVI value, the 6S method has the same tendency as the object's NDVI value in the field.
ESTIMATION OF OIL PALM PLANT PRODUCTIVITY USING SENTINEL-2A IMAGERY AT CIKASUNGKA PLANATION PTPN VIII, BOGOR, WEST JAVA Afifah Nur Rahmasari; Supriatna; Andry Rustanto
International Journal of Remote Sensing and Earth Sciences Vol. 19 No. 1 (2022)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2022.v19.a3775

Abstract

Palm oil is one of the commodities that is growing well in Indonesia with a high commercial value which makes the demand for processed palm oil products increase, it is necessary to have data and technology to estimate the productivity of oil palm plantations more efficiently. Remote sensing technology is one of the technologies that can be used to decision problems spatially and accurately, efficiently, and dynamically. One of them is remote sensing using Sentinel-2A imagery. This study aims to analyze the distribution and the accuracy of the NDVI and ARVI algorithms for the estimation of oil palm productivity at the Cikasungka Plantation PTPN VIII. The estimated productivity of oil palm plantations at Cikasungka Plantation varies in each block with an estimated productivity of oil palm plantations of 35,061 Kg/Ha/Month using the algorithm NDVI and ARVI algorithm is 35,431 Kg/Ha/Month. Oil palm productivity was regressed by vegetation index and plant age to generate a model. Based on modeling with these two algorithms, the accuracy of the ARVI algorithm model has a lower RMSE value than NDVI, so it can be said that it is better in estimation of oil palm plant productivity at the Cikasungka Plantation.
MAPPING BURNT AREAS USING THE SEMI-AUTOMATIC OBJECT-BASED IMAGE ANALYSIS METHOD Hana Listi Fitriana; Suwarsono; Eko Kusratmoko; Supriatna
International Journal of Remote Sensing and Earth Sciences Vol. 17 No. 1 (2020)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2020.v17.a3281

Abstract

Forest and land fires in Indonesia take place almost every year, particularly in the dry season and in Sumatra and Kalimantan. Such fires damage the ecosystem, and lower the quality of life of the community, especially in health, social and economic terms. To establish the location of forest and land fires, it is necessary to identify and analyse burnt areas. Information on these is necessary to determine the environmental damage caused, the impact on the environment, the carbon emissions produced, and the rehabilitation process needed. Identification methods of burnt land was made both visually and digitally by utilising satellite remote sensing data technology. Such data were chosen because they can identify objects quickly and precisely. Landsat 8 image data have many advantages: they can be easily obtained, the archives are long and they are visible to thermal wavelengths. By using a combination of visible, infrared and thermal channels through the semi-automatic object-based image analysis (OBIA) approach, the study aims to identify burnt areas in the geographical area of Indonesia. The research concludes that the semi-automatic OBIA approach based on the red, infrared and thermal spectral bands is a reliable and fast method for identifying burnt areas in regions of Sumatra and Kalimantan.
Sosialisasi Pembuatan Briket Arang Jerami sebagai Salah Satu Sumber Energi Berkelanjutan di Laboratorium Listrik Dasar Fakultas Teknik Universitas Mataram Putra, I Ketut Perdana; Wiryajati, I Ketut; Muljono, Agung Budi; Harjian, M Rivaldy; Adnyani, Ida Ayu Sri; Natsir, Abdul; Supriatna
Jurnal Pengabdian Magister Pendidikan IPA Vol 8 No 4 (2025): Oktober-Desember 2025
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpmpi.v8i4.13086

Abstract

Co-Authors Abdullah Ali Achmad Rifani Adhi Harmoko Afifah Nur Rahmasari Agung Budi Muljono Alfan Zuhair Dinata Andik Isdianto Andry Rustanto Angga Wira Perdana Aries Saifudin Bayu Kusuma Eko Kusratmoko Eva Mauludiyah, Farhan Abdillah Fadila Muchsin Fauziah, Rina Febrita Paulina Heynoek Grace Priscila Silitonga, Hana Gracia, Enrico Hana Grace Priscila S Hana Listi Fitriana Harjian, M Rivaldy Heidiani Ikasari, Ines Helfi Nolia R I Ketut Wiryajati Ida Ayu Sri Adnyani Ihwanul Muslimin Imam Hariadi Indah Prasasti Jacobus Wiwin Kuswinardi Kaluku, Ramli Kuncoro Adi Pradhono Kurniasari, Reni Dyah Yuni Kurniati Rahayuni Liana Fibriawati Listiani, Sevia Maheno Sri Widodo, Maheno Sri Manessa , Masita Dwi Mandini MASITA DWI MANDINI MANESSA, MASITA DWI MANDINI Muhammad Haidar Muhammad Putra Ramadhan Mulia Inda Rahayu Nagasawa, Ryota Natsir, Abdul Niken Hendrakusma Wardani Nurwijayanti Permana, Felix Reza Pin, Tjiong Giok Priambudi, Abiyan Dion Prisca Widiawati Purwadi, Dinda Arisetya Putra, I Ketut Perdana Rafli Syarial Rina Fauziah Rudianto Rushadi, Ifan Seftiawan Samsu Rijal Shidiq, Iqbal Putut Ash Siahaan, Sondang Sopian, Nadya Ata Meiviana Suparmi Suwarsono Syahrial, Rafli Tito Latif Indra Umi Sa’adah Wahida Kartika Sari Wijaya, Fedayeen Dinar Wildan Yahya Suryaditya Yonas Albetian Pangalila Yulingga Nanda Hanief Yumnaristya, Syefiara Hania Yunus Subagyo Swarinoto Zahrul, Zakiul