bluuebunny/crossref_metadata_2025_split huggingface dataset:
Moving Beyond Diesel Generators: Exploring Renewable Backup Alternatives for Data Centers
Authors: Kambhampati Viswambher , Dobbelsteen Andy van den , Schild Joep 
Published: December 2024

Abstract
This study investigates sustainable alternatives to diesel generators for data centre backup power, focusing on renewable diesel (HVO), Hydrogen energy storage (HES), batteries (Lithium-ion and Sodium Sulfur) and Compressed Air Energy Storage (CAES). As environmental scrutiny of data centres grows, the need for cleaner energy sources intensifies. Our research assesses various storage technologies’ energy performance metrics, environmental impacts, and economic feasibility. HVO is a seamless substitute for conventional diesel, compatible with existing infrastructure and less carbon-intensive. CAES offers lower life cycle emissions and operational costs but is geographically dependent. While currently more costly, batteries could achieve better economics with increased operational hours. However, extending the backup duration increases their capital and operating costs significantly, which is less advantageous than other technologies, where only fuel costs increase with longer backup times. For existing data centres transitioning to sustainable energy, HVO is optimal; for new facilities, CAES is ideal if geography allows, with HES as a robust alternative. This analysis offers a pathway for data centres to adopt sustainable, cost-effective energy storage solutions and reduce carbon footprints through on-site renewables or green energy procurement.
Phenological and Spectral Unmixing-Based Identification of Corn Cultivars in Tuban Regency, Indonesia: An Analysis of Sentinel-2 and MODIS Data
Authors: Stefani Olivia , Muhamad Jaelani Lalu , Sumargana Lena 
Published: December 2024

Abstract
In Indonesia, monitoring and mapping corn growth are crucial to promote the implementation of the Government Corn Reserve (CJP) as an alternative for improving national corn management. East Java is the highest corn producer in Indonesia, with Tuban Regency leading the production. According to data from the Central Bureau of Statistics (BPS) in 2024, corn production reached 788,477 tons by 2023. The advancement of technology in the food sector has led to the production of various corn cultivars, such as NK-6172, NK-212, and NK-7328, each with different traits and yields. Therefore, information on corn cultivars is important for predicting the harvest area of corn. Until now, the monitoring of the area and growth of corn in Indonesia has been conventional, requiring considerable time and high costs. Remote sensing technology can be utilized to monitor corn growth and distribution. Linear Spectral Unmixing can identify the distribution of corn areas for each cultivar, where phenology data are used for the date selection of Sentinel-2 satellite images. The results obtained from this study include the corn field area, corn growth phenology, endmember fraction of corn cultivars, and the area of dominant corn cultivars in the research area. The percentages of the dominant cultivars obtained were as follows: NK-6172 at 80.97%, NK-7328 at 15.55%, and NK-212 at 3.48%.
Analysis of 3D Modeling Using LiDAR Velodyne for Tree Inventory Using the LIO-SAM Method
Authors: Adi Triawan Luki , Kurniawan Akbar , Budi Raharjo Agus , Saptarini Dian 
Published: December 2024

Abstract
LiDAR technology has become increasingly popular for tree inventory, particularly when combined with techniques like LiDAR Inertial Odometry and Mapping, or LIO-SAM. LIO-SAM method of 3D modeling analysis for tree inventory using LiDAR is the main topic of this study. Planting trees is one way to lower the amount of carbon in the atmosphere, but doing so requires precise assessments of the trees’ architecture. LiDAR technology overcomes the spatial resolution constraints of satellite photography to enable very accurate three-dimensional modeling of real things. Since tiny LiDAR devices like TLS and Backpack are quite costly, this method was created as a workaround. The Ublox F9R GNSS receiver, Pixhawk orange IMU sensor, and Velodyne vlp 16 LiDAR sensor are the sensors that are used. Accurate point cloud creation is achieved via the LIO-SAM technique, which is subsequently converted into a 3D model of the trees. The precise measurement of tree dimensions required for numerous environmental and forest management applications is made possible by this research’s use of LiDAR. The outcomes demonstrate that the LIO-SAM approach offers excellent 3D modeling accuracy with a minimal average point cloud alignment error. The findings of georeferencing have an RMSE of less than one meter. Furthermore, a robust association has been shown between ground-truth data and 3D modeling outcomes obtained using this approach. The findings of this study can help with efforts to mitigate climate change and improve the management of forests.
Tropical Cyclone Intensity Prediction Using BP-RNN From GPS-Derived Precipitable Water Vapor and Surface Meteorological Data
Authors: Chabibi F F , Putri N S E , Wijaya D D 
Published: December 2024

Abstract
Tropical cyclones frequently threaten tropical coastal areas, making accurate prediction vital. While cyclone track forecasting has improved, predicting cyclone intensity remains challenging. This study uses precipitable water vapor (PWV) and other surface meteorological data to predict wind intensity during tropical cyclone Seroja in southern Indonesia. Data from two GPS stations, CKUP and CRTE, near the cyclone’s path, were analyzed. We employed neural network (NN) algorithms to model nonlinear relationships between variables, utilizing backpropagation to minimize error. The NN was fed with time series data across various hour window sizes (0h, 6h, 9h, and 12h), under the assumption that current parameters influence future conditions. Independent variables included PWV, ZTD, partial pressure of water vapor, temperature, and air pressure, with additional attributes implemented in multiple scenarios. Two years of data (2019-2020) were used to train the model, and wind velocities were estimated during cyclone Seroja. At CKUP, scenario 1 with a 9h window size achieved a probability of detection (POD) of 89% and a critical success index (CSI) of 84%. At CRTE, scenario 4 with a 6h window size achieved a POD of 73% and a CSI of 55%. The root mean square error for predicted wind speed was 1.32 m/s at CKUP and 2.08 m/s at CRTE. This study demonstrates the potential of integrating GPS and meteorological data to enhance cyclone intensity prediction, especially in cyclone-prone regions like Indonesia, offering a valuable contribution to local and global disaster preparedness.
Selogriyo Temple Deformation Mapping in Three Dimensions (3D) Multitemporal Using Terrestrial Laser Scanner (TLS) Technology
Authors: Prasetyo Yudo , Maulana Ashar Wira , Hadi Firman , Bashit Nurhadi 
Published: December 2024

Abstract
Historical buildings such as the Selogriyo Temple are an important part of Indonesia’s cultural heritage. This temple is vulnerable to risks such as environmental changes, seismic shocks, changes in load, and natural aging, which can cause structural deformation. This research aims to analyze the deformation of Selogriyo Temple through multitemporal 3D modeling and highlights the importance of better mapping methods to monitor the deformation of historical buildings. Mapping was carried out using Terrestrial Laser Scanner (TLS) technology to produce 3D deformation analysis using the surface-to-surface method, which was tied to coordinates from GNSS measurements using Total Station Reflectorless (X and Y) and waterpass/leveling (Z). This research also includes the development of more accurate and efficient measurement techniques and the promotion of modern TLS technology. The results include the 3D model of Selogriyo Temple for the second epoch and the surface-to-surface method deformation model, showing measurement accuracy with a distance similarity value of 99.70% compared to the Total Station tool and 99.73% compared to the steel meter. The 3D model has RMSE coordinate X of 0.012 m, Y of 0.0099 m, and Z of 0.005 m. Multitemporal deformation analysis was tested using the T-test at the 95% confidence level, showing an average shift of 0.000332 with a standard deviation of 0.0097. The results of the one-sample T-test show a t-statistic of 0.1869, lower than the critical value of t at the significance level α = 0.05, which indicates the statistical insignificance of the shift. Based on the second epoch 3D modeling, the slope of Selogriyo Temple is still relatively light with a value of 0-1°.
The evaluation of Spatial Planning for Flood Disasters using Sentinel-1 Satellite Imagery (Case Study: Central Java Province)
Authors: Pangi P. , Lan Bagja Izzatur , Budiati Lilin , Prasetyaning Sukmawati Dian 
Published: December 2024

Abstract
Flood disasters are an aspect of spatial planning. The current flood data is in the form of tabular data and point locations. Meanwhile, spatial data in the form of maps of inundation or flood areas is not widely available. Utilization of Sentinel-1 imagery can be used for flood mapping. The analysis results from previous research show that flood data from Sentinel-1 image processing can depict flood inundation areas in a region. This research aims to evaluate spatial planning in Central Java Province against flood disasters. The location of this research is focused on the north coast of Central Java province (PANTURA). The method used to map floods using Sentinel-1 imagery is the Change Detection and Thresholding (CDAT) method. The method for evaluating spatial planning with flood disasters is the map overlay method. The results of this study show that all districts in PANTURA experienced flood disasters in 2017 and 2024. Pati Regency is the district with the highest flood inundation area. Demak Regency is the district with the fastest increase in flood area. The Land Use Plan in the Central Java Provincial RTRW that experienced the most extensive inundation is the fisheries cultivation area. The area with the highest vulnerability is the agricultural area, namely flood inundation increased by 800 hectares over 6 years. Based on the analysis results, it is recommended that the Central Java Provincial RTRW be revised to include areas that are vulnerable to flood inundation.
Identification of Types and Thickness Layers of Seabed Sediments
Authors: Maulana Akbar Rifky , Aldila Syariz Muhammad 
Published: December 2024

Abstract
The sea toll program is one of the developments in the water sector that has a major influence on the areas it passes through. The sea highway acts as sea transportation that is carried out regularly and connects various ports in the territory of Indonesia. With the sea highway, there will be increased activity in the port area which will certainly increase the risk of shipping safety. This encourages periodic mapping and identification to reduce shipping risks that can occur. One of the activities to conduct mapping and identification is by hydrographic survey. There are many acoustic instruments that can be used for mapping the bottom of the water, in this study a sub-bottom profiler and side scan sonar were used. From the results of the study, the depth in the Berlian Terminal dock pool area ranges from 3.1 to 13 meters. The average thickness of the sediment layer from each survey lane is 1.01 m, 0.93 m, 1.41 m, 1.20 m, 1.37 m, 1.86 m, 1.15 m. The results of side scan sonar processing of the seafloor image interpretation produced several features consisting of pitted seafloor, ship grounding, and dredged areas. The distribution of sediment types was successfully classified into three classes consisting of silty clay, silty loam, and silty sand. This result is supported by sediment sampling which shows that the majority of sediment types in the study area was silty.
Spatio-temporal Analysis of Total Suspended Solids Concentration in Porong River Estuary using Sentinel-2 Satellite Imageries
Authors: Bagus Kirmandi Muhammad , Aldila Syariz Muhammad , Qomariyah Lailatul , Heriza Dewinta , Van Nguyen Manh , Garda Denaro Lino 
Published: December 2024

Abstract
The Sidoarjo Mudflow has been channelled into Porong River since its firstly occurred in 2006. The mud endangers the river not only physically due to sedimentation, but also biologically due to mud contamination. Therefore, monitoring of water quality both spatial- and temporally is important to ensure the life below water in the river. The main water indicator for mud is total suspended solid (TSS) which was further used in this study. The TSS concentration was modelled using a simple linear regression and estimated by utilizing Sentinel-2 imageries with limited amount of in-situ water samples. The model was then compared to existing related models quantitatively by means of root mean squared error (RMSE) and normalized mean absolute error (NMAE). The results showed that the stepwise evaluation extracts vegetation red edge band (band 8A) of Sentinel 2 with central wavelength of 865 nm as the best regressor. After the implementation, the model outperforms the existing models with RMSE of 10.893 mg/L.
Sample Size Comparison in Area-Based Image Matching: Cross-Correlation and Mean Relative Gray Value Difference
Authors: Amanina Nabilah , Hariyanto Teguh 
Published: December 2024

Abstract
Geospatial information is data about a specific location with geographic coordinates that can be collected, modified, and displayed in real-time. Geospatial data can be collected through field surveys and aerial photogrammetry. Aerial photos and Digital Elevation Models are the raw results of aerial photography. An orthophoto is a photograph that shows an object in its true orthographic position. The production of orthophotos involves a process that produces stereo images through image matching using various methods. In this research, area-based and feature-based image matching are performed. For area-based image matching, sample sizes of 9×9, 15×15, and 33×33 pixels and two correlation equations were used: Cross-correlation and Mean Relative Grey Difference. Image matching results between samples from the right and left photographs were compared based on the resulting correlation values. From the data processing, area-based image matching with a sample size of 33×33 gives the best results that high Cross-Correlation values and low MRGVD values indicate strong image matching accuracy, especially for images with many details and variations. Thus, the combination of cross-correlation and MRGVD metrics provides an effective and comprehensive analysis for image matching.
Interactive Dashboard for Visualization and Analysis of Landcover Change and Land/Forest Fire
Authors: Adrianto Hari A. , Sitanggang Imas S. , Akbar Auriza R. , Neyman Shelvie N. , Azhim Muhammad F. 
Published: December 2024

Abstract
The study of the earth’s surface is important because it has a major influence on the environment, economy and quality of human life. Land change can occur naturally or due to human activities for settlement, agricultural activities, forest development, and water body development. Currently, land data can be obtained through remote sensing technology such as geographic information systems (GIS) and satellite imagery, but there is no interactive tool that shows land change over time. The purpose of this research is to create an interactive dashboard to visualize and analyze annual or specific period land change data according to user needs. The dashboard is created using the Shiny package available in the R programming language. The research results in an interactive dashboard with features to select the type of graph to be displayed, select the type of land, and select the annual time range. Testing with black box user acceptance testing shows that the developed system has successfully met the expected needs.
Assessing post-fire material degradation: A ship structural analysis case study
Authors: Komariyah S , Lesmana R , Hariadi M R F , Anggara S 
Published: December 2024

Abstract
A bulk carrier ship caught fire while loading fertilizer at the dock, originating from generator of auxiliary engine No. 2 portside. It took approximately 12 hours to successfully extinguish the fire. As the consequence of this accident, the ship suffered significant damage to its structure, machinery, and electrical systems in various areas, including the engine room, superstructure and deck house. A comprehensive assessment was conducted to evaluate the structural integrity of the ship, particularly concerning the post-fire material strength degradation, as well as the impacts of using seawater to extinguish the fire. Destructive tests were carried out on eight material samples taken from parts of the structure heavily affected by fire-induced deformation and from areas that were visually affected by the fire accident. The test results show that there is a decrease in strength of the materials, particularly in areas experiencing slow cooling due to the annealing phenomenon. Areas of the structure exposed to water spray during the firefighting process did not exhibit material embrittlement, as no martensite phase was detected in the microstructure. Additionally, the hardness value remained significantly lower than that associated with the martensite phase.
Evaluation of tol laut in Tahuna and Natuna as underdeveloped, remote, outermost, and border areas
Authors: Kurniawan A , Kharisma A A , Yasadhi K I P , Bahri S , Wirawan A 
Published: December 2024

Abstract
Tahuna (North Sulawesi) and Natuna (Riau Islands) are included in the 3TP (underdeveloped, remote, outermost, and border) areas and use sea transportation to support for their economic activities. High inflation and price disparities are economic problems in this area. “Tol Laut” is government initiative designed to distribute essential basic goods, through a subsidized sea transportation system. These routes connect the economic hub in Java with the 3TP areas. The analysis process uses a mix method, quantitative and qualitative analysis. Port Assessment analysis using weighted scoring, Supply Demand Analysis using index consumption demand, and Regulation Review. To evaluate the implementation of Tol Laut, it focuses on aspects of port location, connectivity, port facilities, potential feeder ships, production performance, hinterland, as well as administration and commerce. Tol Laut in Tahuna can fulfill the supply-demand of essential basic goods significant quantities around 30% from local demand and is supported by the regional government’s commitment, allowing Tol Laut to reduce price disparities. On the contrary, Tol Laut in Natuna can only the supply 16%, resulting inability to control price disparities effectively. There is an urge to optimize and coordinate regarding Tol Laut by involving agencies for the successful enforcement of regulations.
Techno-economic and supply chain model of a small-scale LNG for BMPP in Sambelia
Authors: Abdillah H N , Artana K B , Zakaria M I 
Published: December 2024

Abstract
This paper addresses a method for creating the supply chain model of liquefied natural gas (LNG) to a barge-mounted power plant (BMPP) of 30 MW in Sambelia. This paper conducts the supply chain using a landing craft tank (LCT) ship as the LNG carrier, equipped with a specific principal dimension, and an ISO tank as the LNG storage facility. The use of LCT has the advantage of being able to sail in coastal areas and can be converted using existing ships. This comprehensive techno-economic assessment consists of calculating the LNG demands for the BMPP, the arrangement of ISO containerized tank stacking in the LCT, and identifying the LNG terminal facilities. Moreover, the research points for a future LNG economy are highlighted; cost-effective production and utilization solutions for enhancing the feasibility of LNG. The Landing Craft Tank (LCT), a vessel with a load capacity of 32 container tanks (20 ft) and a volume of 20.38 m3, distributes LNG to BMPP Sambelia. The economic analysis of LNG distribution patterns from Benoa LNG Terminal to BMPP 30 MW Sambelia, using LCT ships with FSRU (Floating Storage and Regasification Unit) receiver terminals, reveals that at a margin of $2.2, the most optimal option has an IRR of 11.6%, a payback period of 5.7, and an ROI of 17.41%.
Pometia pinnata (J.R.Forst. & G.Forst.) as urban tree species: A chloroplast genome and phylogenetic studies
Authors: Salmah N S , Nugroho A , Dwiyanti F G , Siregar I Z , Pratama R 
Published: December 2024

Abstract

Pometia pinnata (J.R.Forst. & G.Forst.) is a native Indonesian forest plant increasingly used in urban landscaping. It produces both edible fruits and valuable timber. As with other tree species, enhancing its genetic quality is essential to maximize the utilization of this promising species. However, the information on genetic and genomic data is still lacking, including the analysis of the genetic relationship of this species. This study aims to generate the chloroplast genome of P. pinnata, identify the most suitable DNA marker, and evaluate the relationship within the Sapindaceae family using long-read sequence data generated by MinION Oxford Nanopore Technologies (ONT). The study involved several steps: DNA extraction, DNA quality and quantity tests, DNA sequencing, assembly of the chloroplast genome, and reconstruction of a phylogenetic tree using three markers, i.e., rbcL, matK, and rbcL+matK combinations. The DNA sequencing yielded 449,068 reads, with 2,856 reads after mapping, an N50 read length of 4,188 bp, a total base of 1,135,927 Mb, and a chloroplast genome of 160,372 bp. These results indicated that the DNA isolated from P. pinnata is good quality. Phylogenetic tree analysis revealed that the combination of rbcL and matK markers effectively differentiates groups within the Sapindaceae family, revealing P. pinnata as closely related to Nephelium lappaceum, Nephelium mutabile, Sapindus mukorossi, Dimocarpus longan, Bligia sapida, Litchi chinensis, Acer yangbiense, and Lepisanthes alata. This study enriches genetic studies on P. pinnata, establishing a foundation for species identification based on the rbcL and matK marker and supporting future tree improvement programs.
The potential of longhorn beetles (Coleoptera: Cerambycidae) as bioindicators at IPB Dramaga Campus
Authors: Haneda N F , Rahmadhani K 
Published: December 2024

Abstract
Insects such as longhorn beetles play a crucial role in the environment as they serve as indicators of ecosystem balance. Longhorn beetles are commonly utilized as bioindicators for assessing ecosystem damage due to their sensitivity to environmental changes. This research aims to analyze the presence of longhorn beetles as potential bioindicators in several stands at IPB Dramaga Campus, namely in the Segitiga Silvikultur (SS), Arboretum FAHUTAN (AF), and Taman Hutan Kampus (THK). The research method employed Artocarpus traps to capture longhorn beetles. The results indicate that the highest abundance of longhorn beetles was found in the THK plot due to the availability of sufficient food sources. The abundance of longhorn beetles was recorded at 27 individuals comprising 5 species, with Acalolepta rusticatrix dominating all research plots. Several factors influencing the presence of longhorn beetles include climatic factors, tree diversity, and human activities. Some longhorn beetle species have the potential to serve as bioindicators of forest ecosystem changes due to their distinctive habitats, such as Sybra fuscotriangularis, Epepeotes luscus, Pterolophia sp., and Ropica marmorata.