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All Journal Journal of Tropical Soils JTSL (Jurnal Tanah dan Sumberdaya Lahan) Journal of Applied Agricultural Science and Technology Jurnal HPT (Hama Penyakit Tumbuhan) Jurnal Pengabdian Masyarakat Biologi dan Sains
Kurniawan Sigit Wicaksono, Kurniawan Sigit
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Environmental Science Immunology & microbiology Physics

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PENGARUH PEMANGKASAN TAJUK TANAMAN KOPI DAN PEMUPUKAN TERHADAP PENCUCIAN UNSUR HARA PADA SISTEM AGROFORESTRI KOPI Nurcholis, Omar; Wicaksono, Kurniawan Sigit; Fata, Yulia Amirul; Kurniawan, Syahrul
JTSL (Jurnal Tanah dan Sumberdaya Lahan) Vol. 13 No. 1 (2026)
Publisher : Departemen Tanah, Fakultas Bio-industri Pertanian dan Kehutanan, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jtsl.2026.013.1.8

Abstract

Tree management such as pruning of coffee canopy and fertilization in coffee-based agroforestry systems plays a crucial role in reducing nutrient losses through leaching. This study aims to evaluate the impact of coffee pruning and fertilization management on nutrient leaching. The study was conducted in a coffee agroforestry system in the Universitas Brawijaya forest from February to August 2023. This study used a split-split plot design with main plots of coffee canopy pruning (T1: pruned coffee, T2: unpruned coffee), subplots of fertilizer type (O: organic fertilizer, A: inorganic fertilizer, M: 50% organic + 50% inorganic), and sub-plots of fertilizer dosage (D1: dosage based on farmer practice, D2: recommended dosage based on the Coffee and Cocoa Research Center, D3: dosage based on the replacement of nutrients removed by the coffee bean harvest). The study had 18 treatments with 4 replicates, resulting in 72 experimental plots. The variables measured included ammonium, nitrate, phosphorus, and potassium concentrations. Sampling of nutrient leaching was conducted four times over a period of six months (February-July), specifically in February, March, April, and July 2023 at 0.5 m distance from the coffee stem in 0.6 m depth of soil. The results showed that pruning coffee plants had a significant effect (P < 0.05) on nutrient losses due to leaching, especially nitrate and potassium. A pruned coffee canopy in an agroforestry system was able to reduce nitrate and potassium leaching by 30% and 13%, respectively, compared to unpruned coffee in the agroforestry land. Nutrient loss of phosphorus through leaching was found to be 21% greater in treatment D1 compared to D2. However, this study did not find a significant effect of the interaction between pruning and fertilization in reducing the leaching of nitrogen, phosphorus, and potassium nutrients.
EVALUASI RANDOM FOREST DAN REGRESI LINIER BERGANDA DALAM PEMETAAN KAPASITAS PENAHANAN AIR TANAH PERKEBUNAN TEH Mukhlisin, Ajral; Wicaksono, Kurniawan Sigit
JTSL (Jurnal Tanah dan Sumberdaya Lahan) Vol. 13 No. 2 (2026)
Publisher : Departemen Tanah, Fakultas Bio-industri Pertanian dan Kehutanan, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jtsl.2026.013.2.17

Abstract

Soil Water Holding Capacity (WHC) is a crucial hydrological parameter for tea plant productivity in hilly terrains. Conventional WHC mapping on a large scale is generally constrained by high operational costs and lengthy analysis time. This study aims to evaluate the performance of Random Forest Regression (RFR) and Multiple Linear Regression (MLR) algorithms in predicting the spatial distribution of WHC at the Wonosari Tea Plantation, Malang. Soil sampling was conducted at 16 observation points using a stratified purposive sampling method based on Land Map Units (LMU). To represent water retention capacity in the effective root zone, undisturbed soil samples were collected vertically at depths of 0–20 cm, 20–40 cm, and 40–60 cm at each point, analyzed using a pressure plate apparatus, and integrated into a single profile average value. Six spectral indices were extracted from Sentinel-2A imagery (NDVI, NDSI, NDWI, LSWI, MSI, NMDI) based on their sensitivity to surface moisture and canopy density, then combined with slope data (DEMNAS) as predictor variables. Given the limited sample size, the RFR model validation was performed using the Leave-One-Out Cross-Validation (LOOCV) method to ensure predictive stability. Results showed that the RFR model with a combination of three key variables (NDSI, MSI, and slope) achieved higher accuracy (R²cv = 0.423; RMSEcv = 1.47%) compared to the MLR model (R² = 0.371; RMSE = 1.59%). Feature importance analysis revealed that slope was the most dominant controlling factor (68.5%). This evaluation concludes that the RFR algorithm is more reliable than MLR for modeling the spatial complexity of WHC in hilly areas. The resulting prediction map effectively divides the plantation into three management zones (High, Medium, Low) to support precision irrigation strategies and soil conservation, potentially increasing operational cost efficiency by 30–40%.
Co-Authors Aditya Nugraha Putra, Aditya Nugraha Anggara, Akmaludin Dimas Brian Rahardi Cahyo Prayogo, Cahyo Christian, Bertolomius Medy Dian Siswanto Didik Suprayogo Ermawati, Ermawati - Fata, Yulia Amirul Istika Nita Iva Dewi Lestariningsih, Iva Dewi Kristiawati, Wanda Lathif, Sarifudin Luchman Hakim Melati Julia Rahma Mewar, Filza Roholesi Mochammad Munir Mukhlisin, Ajral Nurcholis, Omar Riza, Sativandi Rohani, Rosesita Tri Suci Sahiruddin Sahiruddin Sektiono, Antok Wahyu Sukbara, Ghozian Putra Syahrul Kurniawan Utami, Rossi Widhi Wang, Yumin Zaenal Kusuma