Syaiful Anwar

The expansion of Acacia forest plantations in peatland ecosystems in Indonesia has ecological impacts on wetlands and reduces their capacity as high-capacity carbon sinks. To address the decline in ecosystem function in managed peatlands, detailed quantification of carbon stocks is required, using advanced statistical methods based on machine learning applied to satellite remote sensing data. Therefore, this study on Acacia carbon stock quantification was conducted using machine learning, with hyperparameter tuning and cross-validation, on Sentinel-2 Multispectral Instrument (MSI) satellite data from the peatland ecosystem of Rupat Island. Markov Chain Cross-Validation (MCCV) was tested on three machine learning algorithms: random forest (RF), support vector machine (SVM), and eXtreme Gradient Boosting (XGBoost). The measured carbon stock in the Acacia forest plantation (78.46 ± 15.36 Mg C ha-1) and the modeling results indicate that the best algorithm is the RF algorithm (R-squared 0.75, RMSE 13.33 Mg C ha-1, and MAE 10.38 Mg C ha-1) with low error in the test model (R-squared 0.62, RMSE 17.80 Mg C ha-1, and MAE 12.80 Mg C ha-1). Variable importance analysis using SHAP revealed that ANDWI has the highest contribution across the RF and SVM algorithms. The results of machine learning modeling using MCCV on Sentinel-2 MSI data indicate that this method is recommended and requires further testing to improve our understanding of the dynamics of peat carbon stocks under managed Acacia forest plantations.

Tropical peatlands contain large carbon stocks, yet drainage for oil palm plantation (OPP) enhances peat oxidation and increases CO₂ emissions. However, quantitative evidence on site-specific peat heterotrophic respiration (Rh) under mature OPP, as well as how terrestrial and remote sensing (RS)-derived environmental factors regulate it remains limited. This study reported CO2 fluxes representing long-term peat Rh across peat thicknesses and oil palm (OP) proximities under a first-generation mature OPP in South Kalimantan, Indonesia and evaluated the relationships among Rh, chemical and biological peat properties, static terrestrial data, and RS-dynamic drivers across multiple scales. Mean Rh fluxes reached 3.87 ± 0.08 Mg CO₂ ha⁻¹ mo⁻¹ (annual cumulative 46.43 ± 1.06 Mg CO₂ ha⁻¹ yr⁻¹), with significantly higher fluxes observed at locations closer to OP and during the dry season. The interaction of peat thickness, OP proximity, and season influenced Rh. The univariate regression analysis indicated strong relationships among Rh, groundwater level (GWL), and antecedent precipitation. The Quantile Regression Forest (QRF) model captured Rh flux variability (R2=0.63–0.85) with stronger performance when incorporating terrestrial variables. The SHapley Additive exPlanations (SHAP) analysis indicated that distance to OP was the most important contributors on Rh prediction across all scales. The peat characteristic and static-landscape were the important Rh drivers within plot and landscape scales, respectively. This study highlights the importance of scale and seasonal climate variability in shaping Rh dynamics. Also, involving machine learning (ML) and RS datasets in predicting and explaining drivers governing peat Rh under specific peat ecosystems.

The transport of mineral elements from mineral-rich upland soils to lowland peatlands influences biogeochemical cycles and agricultural productivity, yet remains understudied in tropical peatlands. We quantified mineral element input–output budgets in two peatlands by monitoring rainfall, stream discharge, and water chemistry at inlet and outlet points. Both peatlands, located in oil palm plantations, received stream inputs from similar mineral uplands but differed in size and canal length (3632 ha and 195 km for peatland-1; 1478 ha and 48 km for peatland-2). Biweekly water sampling measured suspended and dissolved mineral elements (Al, Fe, Si, Ca, Mg, K), along with dissolved organic carbon and nitrogen. Annual water discharge from peatland-1 and peatland-2 accounted for 20 and 50%, respectively, of the annual rainfall (2082 mm) in each catchment (upland plus peatland), reflecting quick discharge in peatland-2 and greater evapotranspiration in peatland-1. Seasonal changes in elemental concentrations and fluxes were influenced by rainfall, primarily through the dilution of stream water and the transport of organic acid components and mineral elements. Outflows of mineral elements from the peatlands were partially offset by inflows, with mineral elements retained within the peatlands, especially in peatland-1. The size of peatland-1, which was about 2.5 times as large as peatland-2, retained more mineral elements. We conclude that peatland size and canal length are essential features for retaining mineral elements supplied by upstream inputs. Therefore, it is necessary to consider landform and hydrological connectivity to assess mineral element distributions in tropical peatlands.

Additive manufacturing (AM) has progressed from three-dimensional (3D) printing to four-dimensional (4D) printing, which incorporates the time dimension to enable adaptive responses to external stimuli. Nickel–titanium (NiTi) alloys, a shape memory alloy (SMA) distinguished by their shape memory effect (SME) and superelasticity, have emerged as key materials for 4D printing. This review examines AM techniques for NiTi alloys, focusing on Laser Directed Energy Deposition (LDED), Selective Laser Melting (SLM), and Electron Beam Melting (EBM). Each method is analyzed in terms of process parameters, manufacturing challenges, and medical and aerospace engineering applications. The discussion highlights that the thermomechanical and microstructural characteristics of NiTi require precise process control to ensure optimal functional performance. Demonstrated applications in medical implants and lightweight aerospace components underscore the potential of NiTi-based 4D printing for intelligent, adaptive devices. The remaining challenges include accurate prediction of final shapes, ensuring phase homogeneity, and the need for specialized design software. Overall, this study provides insights into the integration of NiTi alloys with 4D printing and identifies key directions for advancing next-generation AM systems. This review presents a unique process–structure–property–application relationship for NiTi-based 4D printing, demonstrating that control of energy input (150–800 W) and scan rate (>1000 mm s ⁻¹ ) directly influences transformation temperature (Af 10 °C–30 °C) and SME strain recovery (3%–6%).

West Bangka Regency, Bangka Belitung Islands Province, is one of Indonesia's main tin-producing areas. Mining activities in this area produce residues in the form of tailings that dominate the post-mining landscape. Tailings are a sand-textured medium with low water retention, unstable aggregate structure, and limited nutrient content. This condition hinders the use of land for ecological reclamation purposes. This experiment examined the effect of the combination of potassium humate and clay-rich soil on improving the quality of tin tailings. The method of experiment was an incubation method, and it was designed in a Completely Randomized Design with two factors. The factors were potassium humate and clay-rich soil. The rates of potassium humate were 0% 0.50%, 1.00%, 1.50% while the rates of clay-rich soil were 0%, 5.00%, 10.0%, 20.0%. The parameters analyzed were organic Carbon (C), Cation Exchange Capacity (CEC), Water Holding Capacity (WHC), and soil pH. The results showed that the combination of 1.50 % potassium humate and 20% clay-rich soil was the best treatment for increasing organic C content to 1.50% and CEC to 7.27 cmol(+)/kg. This treatment also increased the WHC to the level 18.8 %. As for soil pH, the treatment of 1.50% potassium humate without the application of clay-rich soil had the highest value, with a value of 8.02. These findings proved that the integration of potassium humate and clay-rich soils significantly improved the chemical and physical characteristics of tin tailings, thereby increasing their feasibility as a sustainable reclamation medium.

The chemical composition of Fe-Mn-Si shape memory steel continues to be optimized by researchers since Sato and colleagues first reported its shape memory effect in 1982. This work aimed to elucidate the effect of carbon content on the shape memory effect of Fe-14Mn-4Si-8Ni-10Cr steel subjected to a large pre-strain. The shape memory steels were prepared through a process involving melting, hot rolling, cold drawing, and subsequent solution treatment. The recovery strain was measured in solution-treated steels after a large pre-strain of 36% applied via tensile testing, followed by recovery heating at 600 °C. The results indicated that adding carbon up to approximately 0.22 wt% has a beneficial effect on shape recovery strain; further carbon addition to 0.39 wt% degraded the shape memory effect. The maximum recovery strain of 5.72% was exhibited by the steel containing 0.22 wt% carbon. Notably, the recovery strain of the Fe-14Mn-4Si-8Ni-10Cr-xC shape memory steel tested at a large pre-strain of 36% showed values comparable to those tested at lower pre-strains up to 17% for similar steels reported in the literature.

Rangkuti EE, Akhdiya A, Munif A, Siregar IZ, Anwar S. 2025. Tolerance of rhizospheric and endophytic microbes to pesticide residues and their potential for rice growth. Biodiversitas 26: 5267-5276. Rhizospheric and endophytic bacteria are recognized for their ability to enhance plant growth by producing hormones and acting as biocontrol agents. Therefore, this study aimed to identify potential rhizosphere and endophytic bacteria tolerant to three pesticide-active substances. Based on the antagonistic activity against Rhizoctonia solani, Bacillus sp. and Bacillus siamensis isolates achieved the highest inhibitory activities of 81.13 % and 78.55 %, respectively. Bacillus sp., B. siamensis, Acinetobacter radioresistens, and Providencia vermicola were able to solubilize phosphate. Production of Indole-3-Acetic Acid (IAA) was confirmed in Bacillus sp., Bacillus toyonensis, and Acinetobacter radioresistens, and all isolates also possessed the ability to fix nitrogen (N). Based on these parameters, Bacillus sp. and B. siamensis were selected for further analysis. The results showed that Bacillus sp. isolates supported rice seed tolerance to herbicides and insecticides in the range of 5-10 ppm and improved growth in the presence of difenoconazole and glyphosate at 10 ppm. Meanwhile, B. siamensis was tolerant to fungicides in the 5-10 ppm range. None of the selected isolates showed reduced growth after 24 h of incubation in the tolerance test for pesticide contamination. Observably, Bacillus sp. isolate treated with fipronil (5 ppm) was better than the control. It also matched the performance of the control treated with difenoconazole at 5 ppm. These suggested that the selected isolates improved rice growth and tolerance to the active ingredients of the pesticides, contributing to sustainable cultivation practices.

Using peat soils for agricultural purposes is challenged by low fertilizer efficiency, especially potassium chloride (KCl). On the other hand, zeolite is a potential material to produce slow-release fertilizers to improve fertilizer efficiency. This study aims to evaluate and compare potassium leaching from a conventional potassium fertilizer, KCl, and a zeolite-based potassium fertilizer, ZEKA, on peat soil columns. The ZEKA fertilizer was produced using two different zeolite particle sizes: coarse zeolite (ZC) and fine zeolite (ZF). The K leached from the fertilizers was measured in a peat soil column. Three zeolite-based potassium fertilizers were formulated: (1) 40% potassium-impregnated zeolite and 60% KCl; (2) 50% potassium-impregnated zeolite and 50% KCl; and (3) 60% potassium-impregnated zeolite and 40% KCl. Since two different sizes of zeolite were used in this study—coarse zeolite (ZC) and fine zeolite (ZF)—the results of the formulation are referred to as follows: ZC-1, ZC-2, ZC-3, ZF-1, ZF-2, and ZF-3. The experiment was completely randomized with eight treatments and three replications. The treatments were as follows: (1) control, (2) KCl, (3) ZC-1, (4) ZC-2, (5) ZC-3, (6) ZF-1, (7) ZF-2, and (8) ZF-3. The findings revealed that ZC-1 and ZF-1 were the most effective ZEKA fertilizer formulations, with total potassium leached of 1.84 grams and 1.05 grams, respectively. Furthermore, the results showed that the total potassium leached from ZEKA fertilizer was 1.71 grams, while the total potassium leached from KCl fertilizer was 2.83 grams. The results showed that ZEKA fertilizer reduced potassium leaching by around 40% compared to KCl fertilizer. Furthermore, the results of this study can be used to improve the efficiency of potassium fertilizer, particularly in agricultural practices on the peatlands.

The application of stainless steel-clad plates, with or without interlayers, is prevalent in industries such as chemical processing and petroleum due to their enhanced corrosion resistance and cost-effectiveness. This review explores various aspects of hot rolling cladding, rolling temperature, rolling reduction ratio, heat treatment, and mechanical properties including ductility, fracture elongation, yield and ultimate strength, interface characteristics and microstructure. Interlayers significantly enhance the performance and durability of clad plates by improving bonding quality and mechanical properties, acting as diffusion barriers, and evenly distributing stress. Common interlayer materials, including nickel, iron, niobium, molybdenum, copper, titanium, aluminum, vanadium, zirconium, and tantalum each offer specific advantages in enhancing corrosion resistance and mechanical strength. In the rolling process, interlayers play a crucial role in facilitating atomic diffusion and forming strong metallurgical bonds at high temperatures. This review discusses the applications and cost-effectiveness of clad plates, the advantages of interlayers, the role of interlayers in the rolling process, the impact of heat treatment in hot rolling cladding, and the metallurgical bonding mechanism. Overall, interlayers are essential in optimizing the diffusion of alloying elements and the mechanical properties of clad metals, contributing to long-term cost savings and improved product performance.