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Mihwan Sataral
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celebes.gricultural@gmail.com
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INDONESIA
CELEBES Agricultural
Published by Universitas Tompotika Luwuk
ISSN : 27237974     EISSN : 27237966     DOI : https://doi.org/10.52045/jca
Core Subject : Agriculture,
Agriculture, Biological Sciences & Forestry
CELEBES Agricultural: The publisher is the Faculty of Agriculture, University of Tompotika Luwuk. The journal article covers the results of research and policy analysis that can be applied in agricultural practices and sciences such as agronomy, soil science, pests, and plant diseases, entomology, agricultural engineering, agricultural industrial technology, food technology, biology, biodiversity, climatology, animal husbandry, forestry, and socioeconomic agriculture.
Arjuna Subject : Ilmu Pertanian dan Biologi (Semua) - Ilmu Pertanian dan Biologi (Lain-Lain)
Articles 5 Documents
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Search results for , issue "Vol. 4 No. 2 (2024): CELEBES Agricultural" : 5 Documents clear
Monitoring and Visualizing the Impact of the Lapindo Mudflow Disaster Using Earth Engine Apps Platform based on Cloud Computing Dzulfigar, Ali; Ramadhan, Muhammad Ikhwan; Pascawisudawati, Azzahra; Asy'Ari, Rahmat; Setiawan, Yudi; Pramulya, Rahmat
CELEBES Agricultural Vol. 4 No. 2 (2024): CELEBES Agricultural
Publisher : Faculty of Agriculture, Tompotika Luwuk University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52045/jca.v4i2.703

Abstract

The Lapindo mudflow disaster at the PT Lapindo Brantas drilling site in Ronokenongo Village, Porong District, Sidoarjo Regency, East Java caused the loss of agricultural and residential areas. The research aimed to detect the areas that are affected by Lapindo mudflow 2006-2022 using Landsat 7 ETM and Landsat 8 OLI-TIRS imageries, as well as visualize their impact using the cloud computing-based Google Earth Engine/GEE platform. Spatiotemporal data analysis was performed on the GEE platform using random forest machine learning as algorithm for supervised land use classification, while visualization was carried out through Earth Engine Apps. The results showed an increase in the mudflow-affected area from 2006 (204.57 ha) to 2012 (542.32 ha) with northeast direction, whereas the increase was insignificant at the following years. Within the detection period, agricultural land was the most affected area, followed by residential areas and bare land. The area ordering was similar during all detected years. The increasing size of the affected area can potentially have both direct and indirect impacts on the surrounding area. Therefore, special action is needed for the surrounding area, such as relocating settlements to safer areas against the Lapindo mudflow disaster.
AgriForScape Model: Optimization of Agricultural Landscape Design in Karawang District as a Pest Control Strategy with an Ecological Approach Selvianing Tiyas; Wildan Maynardy Wicaksono; Usnil Khotimah; Ali Dzulfigar; Danik Septianingrum; Rahmat Asy’ari; Muhammad Ferdiansyah; Neviaty P Zamani; Rahmat Pramulya; Yudi Setiawan
CELEBES Agricultural Vol. 4 No. 2 (2024): CELEBES Agricultural
Publisher : Faculty of Agriculture, Tompotika Luwuk University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52045/jca.v4i2.710

Abstract

Karawang Regency is one of the national rice barns and a major supplier of rice to Jakarta and surrounding areas. However, the productivity of this rice is threatened by the brown planthopper (Nilaparvata lugens) which causes crop failure. The reliance on chemical pesticides to control this pest results in negative impacts on the environment and endangers human health. This caused a decrease in land productivity resulting in the conversion of land use to non-agriculture. This research aims to analyze the conditions and problems of agricultural areas in Karawang Regency and design a strategy for regulating landscape structures in reducing the intensity of pest attacks in Karawang Regency. Optimizing the structure and pattern of agricultural landscapes using the AgriForScape (Agriculture-Forest-Landscape) model can be one of the effective strategies in pest control to increase land productivity by integrating agriculture and forest land covers. Land cover mapping for 2023 and 2000 was conducted using cloud computing, revealing a conversion of 14,000 hectares of rice paddy land over 23 years, leaving 99,713 hectares. AgriForScape focuses on the integration of agriculture and forest conservation to improve ecosystem balance, increase land productivity, and lower the risk of natural disasters. AgriForScape landscape management can be done with several strategies, including the addition of corridors and forest patches as habitat for natural predators of rat pests, and the addition of refugia areas as food sources and natural habitat for insect pest predators. By applying an ecological approach through optimized agricultural landscape design, this strategy aims to reduce pest attack intensity, boost rice productivity, and contribute to food security and climate change mitigation. The findings are expected to advance sustainable agriculture and offer valuable insights for local governments, farmers, and stakeholders seeking environmentally friendly land management solutions.
Trophic Interaction of Spodoptera frugiperda and their Egg Parasitoids in Agricultural Landscape Kalinyo, Daniel; Andrianto Kupepe; Dendi Ferdianto; Ismail Djamaludin; Hiksa Maulana Saputra; Mihwan Sataral
CELEBES Agricultural Vol. 4 No. 2 (2024): CELEBES Agricultural
Publisher : Faculty of Agriculture, Tompotika Luwuk University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52045/jca.v4i2.717

Abstract

Trophic interactions between Spodoptera frugiperda and its parasitoids are crucial for effective biological control strategies. Understanding these interactions is essential for developing methods that mitigate pest impacts on crops while preserving agroecosystem balance. This study aims to (a) evaluate the interactions between S. frugiperda and its parasitoids, (b) explore the relationship between landscape composition and parasitism levels of S. frugiperda, and (c) analyze how landscape composition influences the food web metrics of S. frugiperda and its parasitoids. The findings identified three egg parasitoid species—Telenomus sp1, Telenomus sp2, and Trichogramma sp—parasitizing S. frugiperda, with Telenomus sp1 emerging as the dominant parasitoid and a potential biological control agent. Notably, landscape composition did not significantly affect the parasitization rate of S. frugiperda eggs. However, the age of maize plants positively influenced the parasitization rate, indicating that older plants may enhance the parasitization of S. frugiperda eggs. Landscape composition, particularly in agricultural contexts, positively influenced Shannon diversity while negatively affecting interaction evenness. In contrast, semi-natural habitats enhanced interaction evenness. These findings highlight the significance of landscape composition in understanding the complexity of the S. frugiperda-parasitoid food web, providing valuable insights for developing pest control strategies for S. frugiperda and conserving natural enemies.
Data Indo InaFire: Spatial Visualization of Peatland Fire Impact and Ecosystem Restoration Monitoring in PHU Jambi using Earth Engine Apps and Sentinel-2 MSI Imagery Muhammad Ilham; Citra Putri Perdana; Verawati Ayu Lestari; Ali Dzulfigar; Hanum Resti Saputri; Danik Septianingrum; Rahmat Asy’Ari; Yudi Setiawan; Rahmat Pramulya; Neviaty Putri Zamani
CELEBES Agricultural Vol. 4 No. 2 (2024): CELEBES Agricultural
Publisher : Faculty of Agriculture, Tompotika Luwuk University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52045/jca.v4i2.737

Abstract

Peatlands formed from long-term accumulation of partially decomposed organic matter in wetland areas. This particular ecosystem is not only capable of sequestering significant quantities of carbon but also vulnerable to forest and land fires (karhutla). Peatland produces considerable CO₂ emissions during fire occurrences, which consequently requires spatiotemporal monitoring to sustain its ecological roles and functions. This study aims to map the severity of fires in peatland ecosystems, estimate the success of post-fire restoration, and develop an Earth Engine Apps-based monitoring platform for peatland fire monitoring. Fire severity assessment and post-fire restoration success estimation were conducted in Jambi's Peat Hydrological Unit (PHU) in 2019 using the Normalized Burn Ratio (NBR) index derived from Sentinel-2 MSI satellite imagery. Most of Jambi PHU's fire severity and restoration levels are high. The area of PHU Jambi with high fire severity was 7,822.91 hectares, while the area with high restoration success was 23,744.69 hectares. NBR monitoring in PHU Jambi can be used to detect fire severity and restore success. The visualization of forest and land fire severity was successfully displayed on the Data Indo InaFire webGIS platform, an Earth Engine Apps-based monitoring platform.
Development of Spatial Platform Based Earth Engine Apps for Mangrove Carbon Stock: Case Study in Serang Coastal Zone, Banten Province Puspitasari, Raditya Febri; Aisyah; Usnil Khotimah; Mahadika Rifka Nugraha; Ali Dzulfigar; Khairani Putri Marfi; Danik Septianingrum; Rahmat Asy'ari; Rahmat Pramulya; Neviati Putri Zamani; Yudi Setyawan
CELEBES Agricultural Vol. 4 No. 2 (2024): CELEBES Agricultural
Publisher : Faculty of Agriculture, Tompotika Luwuk University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52045/jca.v4i2.746

Abstract

Mangroves exhibited considerable potential in mitigating global climate change, as these ecosystems can sequester and store substantial amounts of carbon in the form of live and decayed plant biomass across coastal areas. This research aimed to estimate carbon stocks and assess the dynamics of carbon reserves in the silvofishery area of Serang City, Banten, utilizing geospatial technology and cloud computing. Additionally, the study sought to develop the Indo InaC Data platform to monitor CO2 uptake on silvofishery land. The methodology employed included mangrove detection through unguided classification, and carbon stock estimation was performed using regression models derived from vegetation indices, specifically the Integrated Remote Sensing and Ecological Index (IRECI) and the Transformed Vegetation Index (TRVI). The results revealed fluctuations in mangrove vegetation cover between 2016 and 2023, with a notable decrease occurring from 2016 to 2017, as the cover declined from approximately 61.91 hectares to 50.53 hectares. This decrease was followed by an increase from 2017 to 2022, during which the area rose to 78.1 hectares; however, a subsequent decrease was observed in 2023, with the area reducing to 66.82 hectares. The estimated carbon reserves in the study area for 2023 amounted to 315 tons, reflecting similar dynamics to those observed in mangrove vegetation cover. The development of the Indo InaC Data platform is anticipated to facilitate ongoing monitoring of CO2 emissions uptake, and it is expected to inform future strategies for managing silvofishery land on an annual basis.

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