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All Journal Agrikultura Journal of Degraded and Mining Lands Management SAINS TANAH - Journal of Soil Science and Agroclimatology Caraka Tani: Journal of Sustainable Agriculture
Mochtar Lutfi Rayes
FAKULTAS PERTANIAN UNIVERSITAS BRAWIJAYA
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Education

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Pengaruh Kombinasi Pupuk Organik dan Anorganik terhadap Sifat Fisik dan Kimia Tanah serta Produksi Padi pada Lahan Kering yang Disawahkan Putra, Rizky Eka; Rayes, Mochtar Lutfi; Kurniawan, Syahrul; Ustiatik, Reni
Agrikultura Vol 35, No 1 (2024): April, 2024
Publisher : Fakultas Pertanian Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/agrikultura.v35i1.53686

Abstract

Lahan kering yang disawahkan memiliki proses pelumpuran dan penggenangan yang menyebabkan perbedaan kondisi sifat fisik tanah sehingga menurunkan kesuburan tanah, salah satunya yaitu kerusakan struktur tanah. Upaya untuk meningkatkan kesuburan tanah pada lahan tersebut dapat dilakukan dengan meningkatkan C-Organik, salah satunya yaitu aplikasi pupuk organik (asam amino dan asam humat). Aplikasi pupuk organik yang dikombinasikan pupuk anorganik dengan dosis yang tepat juga berpotensi untuk memperoleh produksi tanaman yang optimal. Tujuan penelitian ini yaitu untuk menganalisis perbedaan karakteristik tanah pada lahan kering yang disawahkan serta menganalisis pengaruh pemberian kombinasi pupuk organik dan anorganik terhadap kesuburan tanah dan produksi padi pada lahan kering yang disawahkan. Penelitian dilakukan di Kebun Percobaan Jatimulyo, Universitas Brawijaya. Penelitian ini menggunakan rancangan acak kelompok (RAK) dengan 9 perlakuan dan 3 kali ulangan. Parameter yang diukur yaitu pH, C-Organik, kapasitas tukar kation (KTK), Kdd, kejenuhan basa, berat isi, tekstur, jumlah anakan produktif, dan berat gabah kering panen. Hasil penelitian menunjukkan terdapat perubahan sifat fisik dan kimia tanah akibat perubahan pengolahan dari lahan kering menjadi lahan sawah. Aplikasi pupuk organik dan anorganik memberikan pengaruh nyata terhadap sifat kimia seperti pH, C-Organik, N-total, P-tersedia, Kdd dan KTK. Aplikasi pupuk organik dan anorganik juga meningkatkan produksi padi sebesar 39-59% dengan perlakuan dosis terbaik yaitu 75% pupuk dasar anorganik + 100% pupuk organik.
Analysis of degraded land suitability and regional comparative advantages for maize development in the Gorontalo sustainable agriculture areas, Indonesia Rayes, Mochtar Lutfi; Nurdin, N; Listyarini, Endang; Agustina, Christanti; Rauf, Asda
Journal of Degraded and Mining Lands Management Vol. 11 No. 1 (2023)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2023.111.4909

Abstract

Maize has attracted the attention of local governments due to its high yield potential and economic prospects, but the strategic value of this commodity has not been specific to particular locations. Therefore, this study aimed to assess degraded land suitability and determine the regional comparative advantages for maize development in the Gorontalo sustainable agriculture areas. The suitability class was assessed using Automatic Land Evaluation System software, while comparative advantages were determined using input-output and regional analysis. The input-output analysis was based on maize farming data from interviews with 80 farmers. This study also employed location quotient, specialization index, and localization index analyses based on maize, rice, and soybean production data for 2014, 2016, and 2018. The results showed that land degradation caused by soil erosion was dominated by moderate, heavy, and very heavy categories. Most of the actual land suitability for maize was classified as marginal suitable (S3) but became very suitable (S1) and moderately suitable (S2) after the limiting factors were improved. Furthermore, maize was profitable for the land suitability classes of S1, S2, and S3, and the commodity was most concentrated in Mootilango District. Based on the results, land management recommendations followed a pattern of recommendation I > II > III > not recommended.
Mesolandform classification and its relationship with smallholder coffee production in the Malang Regency, Indonesia Sholikah, Dinna Hadi; Jamaluddin, Jamhuri; Hasyim, Abdul Wahid; Rayes, Mochtar Lutfi; Aditya, Haidar Fari; Soemarno, Soemarno
SAINS TANAH - Journal of Soil Science and Agroclimatology Vol 22, No 1 (2025): June
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/stjssa.v22i1.93461

Abstract

Mesolandform analysis is necessary for smallholder coffee land management because it can clearly distinguish landform boundaries. Automatic mesolandform classification utilizes geographic information system (GIS) and remote sensing technology using the topographic position index (TPI), slope, curvature, lithology, land use, and normalized difference vegetative index (NDVI). This study aims to classify the mesolandform of smallholder coffee plantations and determine its relationship attributes with coffee production. The data included the Digital Elevation Model, lithology map, Sentinel 2 A harmonized image, and actual coffee production. The spatial analysis was performed using ArcGIS 10.8 and QGIS 3.1.6, and the statistical data analysis was performed using RStudio. Mesolandform affects coffee production (p < 0.0001) and was significantly related to it. The highest production was found on the open slope mesolandform, with coffee production ranging from 7.13 to 9.95 tons/ha. Mesolandform attributes have a significant effect on coffee production increase (R2 = 0.69) on land characteristics with high coffee vegetation density (NDVI > 0.6), topographic position in open slope to flat (TPI 0–2), dominant slope is flat to undulating (<8%), and land curvatures are level or convergent foot slope (<2). The research results can support the sustainable management of smallholder coffee plantations based on mesolandform attributes.
New Emerging and Comprehensive Land Mapping Unit at Detailed Scale: Integrating Random Forest Analysis and Remote Sensing Techniques for Sustainable Land Management Putra, Aditya Nugraha; Ustiatik, Reni; Prasetya, Novandi Rizky; Adara, Erza Aulia; Nita, Istika; Hadi, Syamsu Ridzal Indra; Soemarno, Soemarno; Sudarto, Sudarto; Utami, Sri Rahayu; Munir, Mochammad; Rayes, Mochtar Lutfi
Caraka Tani: Journal of Sustainable Agriculture Vol 40, No 3 (2025): July
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/carakatani.v40i3.97530

Abstract

Precise and detailed land mapping is essential for sustainable land management, environmental conservation, and regional planning, especially in complex and diverse landscapes. This study aims to present an innovative framework for the development of Land Mapping Units (LMUs) at a detailed scale (1:20,000), through the integration of Random Forest (RF) analysis and high-resolution remote sensing data. This study was conducted in the South Malang Plateau, Indonesia (the area characterized by karst, tectonic, volcanic, and alluvial landforms) from June to December 2024. As part of the methodology, the study utilized a combination of geospatial data, including geological maps, DEM-derived topographical indices, and remote sensing indices (Normalized Difference Soil Index/NDSI, Soil Adjusted Vegetation Index/SAVI, Normalized Difference Water Index/NDWI, Modified Soil Adjusted Vegetation Index/MSAVI). A total of 10,903 field observation points were analyzed, with 70% used for model training and 30% for validation. The results show that RF-based LMUs achieved R2 of 0.93 and Root Mean Square Error (RMSE) of 0.645, which is reliable to use. The LMUs provide a comprehensive understanding of landform-specific characteristics, including soil fertility linked to parent material, erosion sensitivity, and slope variability. These insights support applications in precision agriculture, disaster mitigation, and environmental planning. Moreover, the result can guide informed decision-making to prioritize sustainable land management that effectively prevents land degradation in the South Malang Plateau region, as stated in the Sustainable Development Goals (SDGs). The study demonstrates the potential of combining machine learning and remote sensing to refine spatial analysis and address the limitations of manual mapping methods. The proposed framework is scalable and adaptable to other diverse landscapes, making it a valuable tool for advancing sustainable land management in a rapidly changing world.
Co-Authors Abdul Wahid Hasyim Adara, Erza Aulia Aditya Nugraha Putra, Aditya Nugraha Aditya, Haidar Fari Asda Rauf Christanti Agustina Endang Listyarini Hadi, Syamsu Ridzal Indra Istika Nita Jamaluddin, Jamhuri Karam, Daljit Singh Mochammad Munir Nurdin . Prasetya, Novandi Rizky Rizky Eka Putra, Rizky Eka Seca Gandaseca Soemarno Soemarno Sri Rahayu Utami Sudarto Sudarto Syahrul Kurniawan Ustiatik, Reni