bluuebunny/crossref_metadata_2025_split huggingface dataset:
Contribution biochar residue to the role of compost and urea in improving crop yields, soil chemistry properties, and the diversity of soil surface insects in the maize (Zea mays L.) crop land
Authors: Zaitun Zaitun , Sufardi Sufardi , Suwarno Suwarno , Nurahmi Erida , Jufri Yadi , Chaliszar Mohd. , Sah Sabaruddin , Chunaizaturrahmah Chunaizaturrahmah 
Published: December 2023

Abstract
The objectives of experiments were to study the contribution of biochar residue, compost and urea fertilization on crop yields, soil chemical properties, and the diversity of soil surface insects in the maize crop land. The research was conducted at the University Farm Ie Seum Research Station, Aceh Besar District, Aceh Province, Indonesia. There were three treatments: biochar residue (no biochar residue and biochar residue 30-ton ha−1 or 15 kg plot−1), compost (no compost and compost 30-ton ha−1 or 15 kg plot−1), and urea fertilizer (no urea and urea 200 kg ha−1 or 100 g plot−1). The plant yield parameters were corn weight with cornhusk and no cornhusk and corn production with cornhusk and no cornhusk. The soil chemical properties included pH (H2O), total N, available P, organic C, and cation exchange capacity. Soil surface insects were identified using experimental methods, and insects were collected using a pit fall trap (trap barber). The results showed that the combination of biochar residue and compost resulted in the highest corn yields. The combination of biochar residue, compost, and urea fertilizer increased available P, but not pH (H2O), total N, organic C, and cation exchange capacity. Surface insects on the maize plant land consisting of nine genera were classified into five orders: Blatoidea, Coleoptera, Hemiptera, Hymenoptera, and Orthoptera. Genus Aphaenogaster and Camponotus dominated soil surface insects.
Characterization of the essential oil content of lemon (Citrus limon burm f.) peel and the active component of the cohobation waste
Authors: Rienoviar  , Junaidi Lukman , Lestari Nami , Hartanto Eddy Sapto , Sulistyaningrum Anna , Smith Husein 
Published: December 2023

Abstract
Lemon (Citrus limon burm f.) peel is a waste from processing lemons that has not been utilized optimally. One effort to utilize lemon peel waste is by extracting essential oils. In the process of extracting essential oils of lemon peel, a waste by-product will be produced in the form of solid waste (cohobation waste). In order to increase the economic value of lemon peel, it is necessary to evaluate the content of active components in the cohobation waste of the lemon peel extraction process. This study aims to examine the essential oil components in lemon peel and the active components contained in the cohobation waste resulted from the extraction process. The essential oil extraction method used was cohobation. The testing method used was the Gas Chromatography Mass Spectrometry (GCMS). The results showed that the essential oil components extracted from lemon peel were: d-limonene (79.38%), citral (5.98%), neral (3.62%), 3-cyclohexene-1-methanol, α.,α.4-trimethyl-3-cyclohexene-1-methanol (2.94%), linalool (2%), β-myrcene (1.18%), and p-mentha-1,5-dien-8-ol (1.85%). While the results of the cohobation waste test contained various active components, such as: 9,12 octadecadienoic acid (20.66%), g-sitosterol (11.47%), hexadecanoic acid (9.85%), β-bisabolene (9.45%), β-fenchol (7.57%), α-bergamotene (5.47%), vitamin E (2.57%), and campesterol (2.24%).
Comparing avians diversity between two university in Indonesia
Authors: Trissanti V N , Permatasari P A , Setiawan Y 
Published: December 2023

Abstract
IPB University and the University of Indonesia (UI) are two of the many campuses in Indonesia that take part in the UIgreenmetric ranking every year. In 2018, The two campuses were ranked in the top two of UIgreenmetric for national campuses and were committed to going to green campus. This study is important because the campus area in both universities is an area used by students as a place to study, the location of field practicums and research. Besides that, this research can be used as a reference for evaluating and improving environmental conditions at each campus. This study aims to compare the avian diversity on both campuses. Avian data was conducted at the green campus open space using the Ten Species List of MacKinnon and Variable Circular Plot Method. The observation was recorded every morning and afternoon with repetition. The comparison of bird species diversity between IPB Darmaga Campus and UI Depok Campus is included in the same classification, namely the moderate. The higher the number, the higher the species diversity classification. Still, the diversity value is higher in IPB Darmaga Campus at 2.7 compared to UI Depok Campus, which is 2.3.
Corn cob usage as activated carbon using KOH as activator
Authors: Agustina S , Yulianto A , Kamil A , Saepudin A , Fajriyan  , Manurung S E R , Budiyanto  , Majid A , Fitrina A 
Published: December 2023

Abstract
The value of agroindustry waste like corn cob can be added as raw material for produced activated carbon. Activated carbon can be used as adsorbent in food, pharmacy, cosmetic industries, and waste water treatment. This research was conducted by using KOH as activator in the activation process for produced of activated carbon from corn cob. The methods include several steps, first step was particle size reduction. Second step was carbonization process in 500° C for an hour. Third step was activation process using solid KOH and liquid KOH, then heated at 900° C. Then, it will be washed until neutral and dried at 105° C. The activated carbon was observed for iodine adsorption, surface area, carbon content and morphology. The result for activation process using solid KOH: optimum iodine adsorption, optimum surface area, and optimum carbon content were 1233.87 mg/g, 2076.141 m2/g, and 93.59 %, respectively. Activation process using liquid KOH: optimum iodine adsorption, optimum surface area, and optimum carbon content were 595.16 mg/g, 716.271 m2/g, and 95.24 %, respectively. The morphology of activated carbon using solid KOH was cleaner and more open (porous). The Activated carbon can be applied for skin care product, like gel peel off mask.
Mapping forest cover change in relation to oil palm commodities development using Google Earth Engine in the Leuser Ecosystem
Authors: Rafina Ihwan , Prasetyo Lilik Budi 
Published: December 2023

Abstract
The Leuser ecosystem is a vital biodiversity hotspot providing essential ecosystem services to local communities in Asia. It encompasses diverse landscapes, from rainforests to coastal ecosystems and peatlands. However, human activities, particularly deforestation for palm oil plantations, have severely impacted Leuser ecosystem’s ecological balance. This study analyzes land cover changes in Leuser ecosystem between 2016 and 2022, using satellite imagery from platforms like Sentinel-1 and Landsat 8 on Google Earth Engine. During this period, forest cover decreased by 2.8%, while oil palm plantations expanded by 3.15%, with 23,404 hectares of forested land converted. Unregulated activities by small-scale farmers accounted for 73% of this conversion. The accuracy assessment of the land use classification showed moderate accuracy in 2016, with an overall accuracy of 64.95% and a kappa coefficient of 0.388. However, in 2022, the accuracy improved significantly, with an overall accuracy of 73.20% and a kappa coefficient of 0.520. Though land use classification accuracy improved from 2016 to 2022, more robust monitoring and regulation are necessary to address the threats posed by palm oil development. Striking a balance between economic development and environmental preservation in Leuser ecosystem requires sustainable palm oil practices and conservation initiatives.
Detecting land use land cover using supervised maximum likelihood algorithm on spatiotemporal imagery in Samarinda, Indonesia
Authors: Agus F , Prafanto A , Kamil Z A 
Published: December 2023

Abstract
Land use change commonly has an impact on urban areas. The land use and land cover (LULC) model should be used to address land problems. Land conversion is inextricably linked to Samarinda, Indonesia, the administrative center of the province of East Kalimantan. Additionally, this city serves as the new capital city’s Ibu Kota Nusantara-specific buffer zone. The current study aims to find and assess Samarinda City’s LULC. A supervised maximum likelihood technique was used to extract this data from spatiotemporal images. Both spatial and non-spatial data about changes in LULC are used in this study. The imagery data for the Samarinda region includes Landsat 5, 7, and 9 images from 1994 to 2022, along with administrative maps and GPS measurement data enabling on-the-ground checkpoints. Before classification analysis, radiometric and atmospheric correction, cropping, and layer stacking procedures were used to treat the image data. In supervised classification, the maximum likelihood method is applied to the four land classes of uncultivated vegetation, cultivated vegetation, waterbodies, and land with buildings. The research result indicates that the number of uncultivated land classes decreased by 6.38 percent and the percentage of cultivated land decreased by 5.52 percent, according to the study’s findings. On the other hand, the proportion of water bodies increased by 2.39 percent, and the proportion of built-up land classes increased by 9.51 percent. The overall and kappa accuracy test’s average value is 97.67%, higher than the required minimum of 75%.
Forest resilience research using remote sensing and GIS – A systematic literature review
Authors: Risna Rosniati A , Prasetyo Lilik Budi , Lughadha Eimear Nic , Aidi Muhammad Nur , Buchori Damayanti , Latifah Dian 
Published: December 2023

Abstract
Forest resilience assessment is increasingly important given the current global environmental change. However, attributes and indicators to quantify forest resilience still need to be explored. Remote sensing (RS) and Geographical Information System (GIS) techniques are widely applied for forest resilience modeling. A bibliometric analysis was conducted to obtain insights concerning methods for quantifying forest resilience using RS/GIS. VosViewer and Bibliometrix R software were applied to analyze 117 articles from the Web of Science global database covering a period of 2011-2021. Using inclusion-exclusion criteria, 31 studies were examined, covering local, regional, and transnational ecosystem types. Satellite devices were used in 28 studies, whilst GIS dataset frameworks were used in the remaining studies. Multiple satellites and sensors were preferable to maximize results for modeling forest resilience. To estimate resilience, ecological attributes (above-ground biomass, tree-ring, and basal area increments) and remote-sensing derived indicators (vegetation indices, forest cover changes, deforestation rates, and forest productivity) were analyzed using conventional statistical tests or machine learning techniques. Studies combined experiments, observations, and process-based models demonstrated better results. Scale and resolution, indicator uncertainty, and data availability were among the constraints reported using RS/GIS. Therefore, a standardized framework for forest resilience assessment incorporating field observation with RS/GIS is needed.
Reducing methane and nitrous oxide production in different soil types through utilizing Turmeric Rhizome (Curcuma domestica Val)
Authors: Harsanti Elisabeth Srihayu , Wihardjaka Anicetus , Ardiwinata Asep Nugraha 
Published: December 2023

Abstract
Indonesia is rich in flora diversity which is used to support agricultural development. One of the useful plants in agricultural cultivation is turmeric rhizome. Turmeric rhizome (Curcuma domestica Val) is a natural ingredient that can function as an inhibitor of the production of methane and nitrous oxide in the soil. A laboratory experiment aimed to determine the potential of turmeric rhizome on the production rate of CH4 and N2O in different soil types. The experiment used a completely randomized factorial design with 3 replications, the treatment was soil type factor and nitrification inhibitor factor. The rate of GHG production (methane and nitrous oxide) in the application of nitrification inhibitors (NI), both natural (turmeric rhizome) and commercial (DCD) was lower than without the application of NI on Inceptisols, Vertisols, and Alfisols. Turmeric rhizome natural ingredients provide promising prospects that are cheap and easy to obtain as an inhibitor of the rate of CH4 and N2O production for paddy fields.
Use of coal ash- and lignite-enriched compost to improve soil biological properties and reduce pineapple disease in Ultisols of Central Lampung
Authors: Widyastuti R , Iskandar I , Ratdiana R , Raniah D L 
Published: December 2023

Abstract
Ultisols used for pineapple cultivation are classified as suboptimal lands because of their low soil fertility. Application of compost enriched with other soil ameliorants, such as coal ash in the form of fly ash, bottom ash (FABA), and lignite, can be a good alternative to improve soil properties, including increasing the soil microbial and fauna populations, which play an important role in improving soil fertility and reducing the incidence of pineapple disease. The purpose of this study was to investigate the effects of FABA- and lignite-enriched compost on microbial and earthworm populations and the incidence of pineapple disease. FABA- and lignite-enriched compost at a dose of 50 tons/ha was applied using a spread-and-row technique in the pineapple plantation area in Central Lampung. The parameters observed included the microbial population (Pseudomonas, Bacillus, Actinomycetes, Trichoderma), functional microbial populations (nitrogen-fixing bacteria, phosphate-solubilizing microbes, siderophore producers), earthworm population, and incidence of pineapple diseases (marbling, brown spot, cork spot, and pink diseases). Generally, all treatments with FABA- and lignite-enriched compost showed better results than the control for all observed parameters. The treatment of FABA-enriched compost applied with a row technique was the best compared to other treatments because it tended to increase the population of Pseudomonas, Bacillus, Actinomycetes, and nitrogen-fixing bacteria, as well as earthworm abundance and biomass. In addition, in this treatment, there was no incidence of pineapple fruit disease. The abundance of earthworms and soil microbes, especially Pseudomonas was one of the factors which can create a healthier soil ecosystem to suppress the incidence of pineapple diseases.
Transformation of the p53 plasmid carrying Cas9 to Chili Callus (Capsicum annum) via Agrobacterium tumefaciens
Authors: Bagus F R M , Nova B , Syukur S , Jamsari J 
Published: December 2023

Abstract
Geminivirus is a virus that causes curly yellow disease in chili plants, which causes yield losses ranging from 20-100%. CRISPR/Cas9 facilitates the development of virus-resistant plants using genetic engineering technology. In this study, the process of transferring the plasmid p53/Cas9 to Agrobacterium was executed using the freeze-thawing technique. To validate the achievement of the transformation, an amplification process utilizing specific primers and an in-out primer combination was performed. We have achieved a transformation efficiency of 60%, as indicated by the PCR detection analysis of the putative recombinant callus. This outcome serves as a crucial starting point for the subsequent stages involved in transforming the p53 plasmid containing the Cas9 gene into chili (Capsicum annum) via Agrobacterium tumefaciens.
3D Kriging interpolation for traffic noise visualization: designing noise observation points and valuation of spatial interpolation accuracy
Authors: Wickramathilaka N , Ujang U 
Published: December 2023

Abstract
Identifying the risk of traffic noise is vital in minimizing traffic noise pollution in urban areas. As noise travels in every direction, 3D visualization of traffic noise is essential, which involves visualising traffic noise along the facades of buildings. A standard traffic noise model is necessary to calculate traffic noise levels, as several factors affect traffic noise. Moreover, designing noise observation points in 3D and spatial interpolation play significant roles in 3D noise visualisation. Therefore, this study demonstrates the results by elaborating on the spatial interpolation and designing noise observation points. A noise observation point consists of four parameters in 3D space. Generally, Inverse Distance Weighted (IDW), Triangular Irregular Network (TIN), and Kriging do not support the interpolation of four parameters in 3D. However, 3D Kriging in Empirical Bayesian Kriging provides significant opportunities to interpolate noise levels in 3D. However, the elements of the function of spatial interpolations are vital for accuracy. The 3D Kriging uses different variograms according to semivariance. This variogram directly impacts the weighting factor of 3D Kriging. Therefore, this study develops a comparison to identify the impact of different variograms on the accuracy of 3D Kriging interpolation on traffic noise.
Adaptation 4D and 5D BIM for BIM/GIS data integration in construction project management
Authors: Wan Abdul Basir Wan Nor Fa’aizah , Ujang Uznir , Majid Zulkepli 
Published: December 2023

Abstract
Construction project management contains a sequence of activities such as planning, completing, scheduling and cost estimation. Building Information Modelling (BIM) is one of the technologies that can be used to manage the complexity of construction documentation. BIM provides a digital visualization of building structures in three dimensional (3D) and store all the geometric and semantic data likes construction element, material properties, construction details, and schedules but lacking feature like geospatial analyses. Geographic Information System (GIS) can apply in construction project to overcome the limitation because GIS can offer advantages in route design, cost estimation, site layout, material layout design and construction planning. Therefore, integration BIM/GIS is recommended to produce an operational of construction project management. This paper presents the advantages of BIM-based in term of scheduling (4D BIM) and cost estimation (5D BIM) in the scope of project management to control the time efficiency and cost saving during the construction process. 4D and 5D BIM data were examine during data integration between BIM and GIS by using Feature Manipulation Engine to bring the gap in construction project management. 4D BIM data develop using Naviswork while 5D BIM developed using Autodesk Revit. GIS data management was used to maintain and update the construction database to assist the project planning.
An overview of predictive maintenance in relation to 2D and 3D Geographical Information System (GIS) for built environment
Authors: Hairuddin F I , Azri Suhaibah 
Published: December 2023

Abstract
Well-preserved buildings can be a great asset to the country, contributing to its economic growth. The lifespan of a building and its assets can be extended through proper maintenance. This will improve the longevity of its function, sustain its performance, and optimize maintenance costs. Predictive maintenance is a proactive approach to maintenance, as it is conducted based on the current operational state of equipment rather than average life statistics. It is generally implemented in building maintenance, machinery, and many other industries. While predictive maintenance has grown in application with artificial intelligence, digital twins, and machine learning, its application with geographical information systems (GIS) and 3D GIS have limitedly discussed. Geospatial predictive maintenance can be realized by integrating the asset's location with its maintenance semantic and temporal information. By incorporating geospatial thinking into the predictive framework, it can help optimize decision-making processes such as allocating maintenance costs based on calculating affected areas, visualizing the location of assets, understanding their interactions with meteorological events and virtual situations. Therefore, this paper will discuss a review of predictive maintenance in relation to GIS and 3D GIS.
A review of satellite-based monitoring of groundwater storage changes and depletion consequences
Authors: PengZhen Liu , Md Din Ami Hassan , Hamden Mohammad Hanif 
Published: December 2023

Abstract
Groundwater demand is increasing due to global population growth, climate change and rapid urbanization, however, poor planning and over-exploitation are leading to rapid depletion of groundwater, which in turn causes adverse impacts such as land subsidence, soil salinization and water quality deterioration. Groundwater storage (GWS) monitoring is essential to the sustainable management of regional water resources and the prevention of environmental and social issues associated with depleted groundwater resources. Conventional groundwater observation is primarily conducted through groundwater well-level measurements, which requires a lot of time and effort, and is insufficient to accurately reflect GWS changes regionally and monitor large-scale groundwater level changes. The availability of various satellite data makes it easier to study groundwater information effectively. The aim of this paper is to first review the seriousness of groundwater depletion, every year, 15% to 25% of the total global groundwater extraction is overexploited. Then, based on satellite geodetic technologies such as Gravity Restoration and Climate Experiment (GRACE), GRACE Follow-On, Sentinel-1, and Global Navigation Satellite System (GNSS), the basic principles of GWS monitoring are expounded. The reliability of the monitoring results was analyzed through the literature summary, showing that the results were basically consistent with the trends reflected by the measured groundwater samples, and the statistical significance of quantitative comparisons was higher than 0.65. The impact of the consequences of groundwater depletion also deserves our attention. This paper combined with multi-source satellite and tidal data, etc., the feasible research methods are discussed for a series of adverse consequences caused by groundwater depletion.
A review on the GIS usage in spatio-temporal risk assessment in asset management
Authors: Syafiq M , Azri S 
Published: December 2023

Abstract
Risk assessment for asset management is a process to analyse the potential risk that could affect the efficiency of operating assets. An effective risk assessment strategy depends on high-quality data and effective data analysis. To do so, risk assessment should take into consideration the spatial and temporal aspects of risks of physical assets in asset management for a data-driven decision-making. Failure to incorporate the spatial and temporal aspects in risk, when the risk possess spatio-temporal correlation, could lead to a defective estimation of assets risks. GIS can be used to analyse multidimensional information which includes 3D GIS, and spatio-temporal data (2D+t and 3D+t). Due to its superiority in handling multidimensional data, GIS is often a preferable tool to collect, manage, manipulate, and visualize spatio-temporal data to allow an accurate and informed analysis. The aim of this study is to uncover the use of GIS for risk assessment in asset management when spatial and temporal data are concerned. This study conduct a thorough review of previous research to look into the current development of asset management that utilizes a spatio-temporal approach for data collection, analysis, and 3D visualization for risk assessment. At the end of this study, we found that physical assets are affected by risk that possess spatio-temporal correlation. Several GIS techniques for data collection, analysis and visualization are found to provide a more effective analysis for assessing spatio-temporal risks. This paper concludes by providing a workflow that can be used by asset managers to assess risk spatio-temporally based on the findings of this study.