bluuebunny/crossref_metadata_2025_split huggingface dataset:
Persistence of the high solar potential in Africa in a changing climate
Authors: Soares Pedro M M , Brito Miguel C , Careto João A M 
Published: October 2019

Abstract
The African continent faces several challenges and threats: high vulnerability to climate change, the fastest population increase, the lowest degree of electrification and the need for an energy transition towards renewable energies. Solar energy constitutes a viable option for addressing these issues. In a changing climate the efficient implementation of solar capacity should rely on comprehensive information about the solar resource. Here, the newest and highest resolution regional climate simulation results are used to project the future photovoltaic and concentrated solar power potentials for Africa. We show that the high potentials for solar energy will not be reduced much throughout Africa with climate change. However, the PV solar potential is projected to decrease up to about −10% in limited areas of eastern central Africa; increases are also projected to the northwest and southern Africa (up to about +5%). These changes are mostly determined by changes in solar irradiance but in certain areas the warming is a critical factor limiting PV potential.
Genetic Algorithms Optimization for Water Management in Irrigated Paddy Fields
Authors: Arif Chusnul , Setiawan Budi Indra , Mizoguchi Masaru , Nugroho Bayu Dwi Apri 
Published: October 2019

Abstract
Water management in paddy fields is main key to produce more yield and mitigate greenhouse gas (GHG) emissions at the same time. Commonly, Indonesian farmers apply continuous flooding irrigation to combat weed growth and gain maximum yield as well. However, this method is less efficient in water use and releases more GHG emissions as represented by Global Warming Potential (GWP) value. The System of Rice Intensification (SRI), as alternative rice farming, applies intermittent irrigation that has possibility produce more yields with minimum GHG emissions. However, optimum water management for these purposes is not clear yet. The objective of this study was to search optimal soil moisture and water depth in each growth stage using genetic algorithms (GA) model for SRI rice farming. GA model was developed based on one rice season experiment that was conducted during January to May 2018 with three water management regimes, i.e., flooded (FL), moderate (MD) and dry (DR) regimes, respectively. Based on the experiment, MD regime produced highest yield by 5.26% and 10.89% higher than those FL and DR regimes, respectively. So this was the best regime among others. However, this regime release more GHG emissions than that DR regime in which its GWP value was 87.85% higher than that DR regime. So, the GA model was used to find the better regime than that MD regime. Based on those empirical data, GA model found optimal soil moisture and water depth in four growth stages. Based on GA optimal scenario, the yield can be increased up to 1.31% higher than that MD regime and GWP can be reduced up to 8.62% lower than that MD regime. More field experiments are needed to validate the model under various climate conditions.
Artificial neural network based particle swarm optimization in predictions mortality rate of broiler chicken
Authors: Hasman D , Gustian D , Saputra R B , Rahmasari H , Lorentina  , Ratnasari S A 
Published: October 2019

Abstract
Success in broiler farms can be assessed from the mortality rate of chickens and also a solution to reduce the mortality rate of chickens. But in the process there are obstacles that is the death of hickens that tend to fluctuate so that of course resulted in financial losses for farmers. To prevent it required a method that can predict and control the mortality rate of broiler chickens. In this research, data mining method used is Artificial Neural Network (ANN) based on Particle Swarm Optimization (PSO), to produce accurate prediction with excellent iteration and also small error rate. The results of analysis in predicting mortality rate of broiler chickens by artificial neural network method in combination with Particle swarm optimization get better RMSE result (0.135) than Artificial Neural Network have not been optimized (0.381) with january mortality data and result of application quisioner made value 83,125 which can be categorized well and enough help the farmer in controlling prediction of chicken mortality rate broiler.
Adaptive Neuro-Fuzzy Inference System implementation for farmer’s term of trade forecasting in West Sumatra
Authors: Aufar Y , Sitanggang I S 
Published: October 2019

Abstract
The farmer’s term of trade (NTP) is used by the Central Bureau of Statistics (BPS) as one of the indicators for measuring the level of welfare or purchasing power of farmers. To prepare preventive measures when the NTP index falls from the previous period, the relevant parties need to predict NTP for the coming period. The purpose of this study is to measure the performance of Adaptive Neuro-Fuzzy Inference System (ANFIS) in predicting NTP of West Sumatra Province in the coming month. The data used are monthly NTP data of West Sumatra Province obtained from the BPS website www.sumbar.bps.go.id from 2013 to 2016 for the network training process. Model evaluation was done by comparing the test results with actual data in 2017. Forecasting systems are divided into two types, namely time series model and the multivariate model. The test results show that the time series model has the smallest RMSE of 0.3430 for the training set and the RMSE value is 1.4570 for the testing set.
Mapping of palm oil technology based on patent information analysis
Authors: Wibowo M H , Fauzi A M , Taqi F M 
Published: October 2019

Abstract
Patent system has been implemented globally to protect intellectual property in technology. Patent information analysis has been used for various purposes, including technology mapping, technology forecasts, business intelligence, patent portfolios, and others. Indonesia is the largest producer and exporter of palm oil in the world thus palm oil is one of Indonesia’s largest foreign exchange earning commodities, but Indonesia’s palm oil research activities are still lagging behind Malaysia. This study aims to map the conditions and development of palm oil technology in the world and Indonesia based on patent information analysis that expected to be an input for researchers & policy maker (government, university, R&D institution) in structuring of research and development strategic planning to produce applicative researches which suitable to industry needs. Patent information analysis of palm oil in this study includes technology life cycle, technology classification, patent applicants, market size of technology, and experts of palm oil technology. Mapping of palm oil technology based on patent information analysis in this study shows the development of palm oil technology both in the world and Indonesia are in the stage of growth. In the period 1997-2016, technologies that were widely developed were production of oil and fat from palm oil raw materials and enzyme utilization for synthesis of organic compounds, processing of wastewater and fertilizers from palm oil waste, cultivation or nursery of oil palm, herbal preparations, and utilization of oil palm biomass for particle board. Data on patent applicants for palm oil in the world shows that 83% of patent applicants came from companies, where the Malaysian Palm Oil Board (MPOB) is the largest producer of palm oil technology in the world.
Antioxidant activity and phytocemical analysis from black rice bran
Authors: Muniroh Amirotul , Budijanto Slamet , Pontjo Priosoeryanto Bambang 
Published: October 2019

Abstract
Black rice bran is a one of potential antioxidant component source. Black rice bran bioactivity is better than white rice bran. However, the high bioactivity of black rice bran is not accompanied by its utilization as a functional food ingredient. The ability of R. oryzae to degrade lignocellulose and polysaccharide matrix through its enzyme activity is proven to increase antioxidant activity on rice bran variety of white rice. The capability of these molds on the black rice bran matrix is expected to maximize the potential functional properties of antioxidants. This study aims to determine the content of phytochemicals and antioxidants from black rice bran and the comparison between before and after being given fermentation treatment with addition of Rhyzopus oryzae. In this study, black rice bran was given two different treatment that is non-fermentation and fermentation using Rhizopus oryzae for 96 hours. After the cultivation period, each sample was extracted with methanol solvent. Further phytochemicals including flavonoid, alkaloid, tannin, saponin, quinone, steroid and triterpenois were evaluated by qualitative phytochemical tests while the antioxidant capacity was evaluated by DPPH assay. The results showed that the fermented black rice bran samples contained flavonoids, saponins and triterpenoid while non-fermented black rice bran sample contained flavonoids, tannins and steroids. Antioxidant activity of fermented black rice bran (67,37%) was more effective to inhibit free radicals than non fermented black rice bran (43,93%). According to the result, studies are needed to produce a black rice bran functional food product that can be used as a source of food containing bioactive compouns and antioxidants.
ICTs for small scale farmers in Indonesia: how to make it possible?
Authors: Seminar A U , Sarwoprasodjo S 
Published: October 2019

Abstract
The effort to digitalized agricultural process has been started since the 1980s to maximize the food production, yet this effort majorly targeted agricultural industries or state-supported farmers group. In Indonesia, the number of small independent farmers is high. These small farmers have little access to ICT infrastructure to support their farming activities. This paper seeks to propose strategies for improving small independent farmers’ access to and utilization of ICTs for agriculture. Qualitative method is used to identify the problems and needs of small farmers and their perception of ICTs for agriculture. Using multi-sites ethnography strategy in gathering data, we conducted in-depth interviews with 22 small farmers from 12 regions in Indonesia. We also observed the day-to-day activities of small independent farmers in two villages in Bogor and Yogyakarta, Indonesia. We found that several strategies have to be considered for developing ICTs for small scale farmers, which are (1) analysing small farmers perception about technology; (2) identifying local-specific issues; (3) involving small farmers in planning digital agriculture system; (4) facilitators of new technology must have communicative competences or communicative skills so the planning of digital agriculture system is done through participatory approaches.
Canopy cover of mangrove estimation based on airborne LIDAR & Landsat 8 OLI
Authors: Prasetyo L B , Nursal W I , Setiawan Y , Rudianto Y , Wikantika K , Irawan B 
Published: October 2019

Abstract
Mangroves are very important ecosystems, because of their economic value and environmental services, including as a habitat for various wildlife species, storing carbon, and protecting land from sea abrasion. Indonesia is known to have large mangrove area and diversity. It is estimated that the area of mangroves in Indonesia in 2015 reached about 3 million hectares, with 15 families, 18 genera, 41 true mangrove species and 116 species of mangrove associations. Unfortunately, the area to continue to decline due to degradation and conversion to other land uses, especially ponds and built up areas. Usually, mangrove degradation assessment is carried out by field survey and relying on Normalized Difference Vegetation Index (NDVI) clustering derived from satellite image data. Field surveys require a large amount of time and cost, meanwhile NDVI clustering is either inaccurate or too rough. Therefore, exploration of another methods are needed. Our result showed that pixel value of Band 5, Band 6, NDVI and PC1 can be used to estimate canopy cover. Regression using quadratic equation is better than linear equations. However, we noticed limitations of optical Landsat 8 OLI data for canopy cover mapping, namely pixel saturation on high canopy cover and high pixel value of bush/shrubs/regrowth that was not always representing high canopy cover.
Bycatch assessment for fusilier gillnet to support ecosystem approach fisheries management
Authors: Mosse J W , Hutubessy B G , Pailin J B , Rumbouw B. 
Published: October 2019

Abstract
Fusilier (Pisces: Caesionidae) gillnet, called jaring lalosi, have been used since decades by fishers from Assilulu village, meanwhile its scientific information is limited. The aim of this study is to learn the reef fish species selectivity of jaring lalosi and to assess its bycatch using productivity and susceptibility assessment (PSA). This study was conducted at Pulau Tiga waters, Central Maluku Regency, for 3 months observation: October 2017, February and April 2018. Jaring lalosi which means fusilier gillnet, caught dark-banded fusilier, Pterocaesio tile, 94.4% of the total catch. The rest of the catch we represented as by-catch of jaring lalosi. As a high resilience and low vulnerability species, the sustainability of dark-banded fusilier fisheries is unlikely to be fully concerned. As high mobility schooling species, dark-banded fusilier was caught at different communities of reef fishes. MDS analysis showed discrepancy of species selectivity of fusilier gillnet by monthly catch rate. The PSA for bycatch resulted 2 reef species are least likely to be sustainable, 12 reef species are most likely to be sustainable on the criteria of recovery axis and 3 pelagic species are the most sustainable species. We concluded that the practiced of jaring lalosi has low impacts on reef fish community and tendency to overfishing is almost none as long as there is no increasing on fishing pressure. For the implementation of fisheries management based on ecosystem approach (EAFM), bycatch assessment should be applied to other fishing gears.
Effectivity of rearing with difference composition of feed toward body weight gain of mud crab Scylla olivacea in the mangrove area, Tuhaha Village, East Saparua, Central Maluku-Indonesia
Authors: Pattiasina B J , Natan Y , Tetelepta J M S , Ongkers O T S , Pattikawa J A 
Published: October 2019

Abstract
This study was aimed to determine the level of weight gain of adult mud crabs given different doses of feed at the front of the mangrove area in Tuhaha Bay, Central Maluku Indonesia. Mud crabs (Scylla olivacea) with average initial body weight (BW) of 100.36±8.35g g were placed in a plastic basket measuring 50 x 25 x 17 cm³ which hanging on bamboo raft. Prior to measurement, the crabs were acclimatized for one week at the location with 3% feeding/BW. Treatment with three different fish feed doses i.e., 5% trash fish: 5% mashed raw papaya (Treatment A), 7.5% trash fish: 2.5% mashed raw papaya / BW (Treatment B) and trash fish 10%/BW (Treatment C). Each treatment consisted of 6 individuals as replicates. Data collection includes absolute BW and Specific Growth Rate (SGR). Data were analyzed using descriptive statistic and displayed in tables and graphs. The results showed that mud crabs given treatment A, B and C had an average BW of 95.03±2.84g, 100.22±3.81g and 114.83±2.55g, respectively. Relative BW gain and SGR of treatment B was higher than those of treatment A and treatment C. These results indicated that treatment B is quite effective in meeting the energy needs for increasing the body weight of individual crabs at this location.
Status of mud crab (Scylla sp.) fishery and mangrove ecosystem of Sanleko Village, Buru District, Indonesia
Authors: Tetelepta J M S , Lopulalan Y , Pattikawa J A 
Published: October 2019

Abstract
Until recently live crab business has been proven as a promising fisheries practice in many parts in Indonesia. Mud crab capture based fishery at Sanleko Village has been going for more than 20 years of time. The present study was aimed to examine the status of mangrove ecosystem as main mud crab habitat and mud crab fishery at Sanleko Village of Buru District. Mud crab fishery status was considered less sustain with an average sustainable scale of 47.36% whilst mangrove ecosystem sustainability status was considered sustain (60.29) according to the ecosystem approach to fisheries management. The economic analysis shows the NPV of 17.05 with average B/R of 2.47. The IRR of this fishery was 23.2% which is bigger than the interest rate of 15% and the payback period of 0.6. In general, the fishery of mud crab at Sanleko Village is still feasible with steadily decreasing economic sustainability.
Advancing reef coral diagnostic capabilities using molecular biotechnology and artificial intelligence
Authors: Mayfield A B 
Published: October 2019

Abstract
Coral reef ecosystems around the planet are threatened by an onslaught of anthropogenic stressors, most notably global climate change (GCC); indeed, no regions have been spared from our wide-ranging human impact. Consequently, there has been an urgent push to 1) model how marine organisms will respond to future changes in their environments and 2) make data-driven predictions as to which populations are most stress sensitive. Given our recently elevated level of understanding of the responses of reef-building corals to environmental change and GCC, we are now in a position in which it may be possible to make projections as to which corals are most susceptible to GCC, as well as which will likely demonstrate resilience. Herein I explore the potential for data-trained predictive modeling approaches based on artificial intelligence to generate models that can accurately predict coral stress susceptibility (CSS). Specifically, I advocate that coral reef-focused partial least squares and neural networking algorithms (trained with either molecular or environmental data) should be developed, with their prognostic capability then field-tested at sites that span a gradient of human impact and ecological resilience in the high-biodiversity “Coral Triangle.” If the developed predictive models are characterized by the analytical capacity to forecast CSS, we will possess one means of identifying reefs that should be prioritized for conservation in this era of rapidly changing global climate.
Zooplankton seasonal dynamics in Ambon Bay, Maluku
Authors: Mulyadi H A , Saputra F R T 
Published: October 2019

Abstract
A seasonal study of zooplankton was conducted to understand the abundance and diversity of zooplankton in related to oceanographic condition in Ambon Bay, Maluku. The research was conducted in four months (March, April, July, and October) which represented the various seasons in Ambon Bay in the year of 2016. The abundance of zooplankton was determined from NORPAC net (mesh size 0.33 mm) with depth varied from 10m to surface. The samples were taken in 18 stations which 7 stations located in Inner Ambon Bay, 1 station in the sill, and 8 stations in Outer Ambon Bay. All samples were preserved in bottle containing 4% formaldehyde and then analyzed using microscope. We also used CTD equipment to measure the vertical and horizontal distribution of temperature and salinity from the surface into 10m depths. The result showed that the distribution of temperature and salinity in Ambon Bay were varied following the season. The total abundance of zooplankton in Ambon Bay was fluctuated between 403-42097 ind./m3 following the season. The highest average abundance of zooplankton occurred in March (northwest monsoon) where the temperature was higher than other season. The lowest average abundance occurred in April (transition) where the salinity was lower than other season. The number of Copepods from genus Acrocalanus and Eucalanus were presented in all season. In southwest monsoon, spawning of Annelida and Echinoderm larvae were the most indicated larvae. Meanwhile, in southeast monsoon we indicated that the Copepod eggs and larvae as the most abundance in the waters.
Kelvin wave propagation along the southern coasts of Sumatra, Java, and Lesser Sunda Islands generated by Madden-Julian Oscillation (MJO) Phase 3
Authors: Ningsih N S , Kusmarani A M , Hanifah F 
Published: October 2019

Abstract
Kelvin wave propagation along the southern coasts of Sumatra, Java, and Lesser Sunda Islands generated by the Madden-Julian Oscillation (MJO) phase 3 (April 28 – May 6, 2004) has been studied by using sea surface height anomaly (SSHA) data simulated by a 1/8° global version of the HYbrid Coordinate Ocean Model (HYCOM), satellite-observed outgoing longwave radiation (OLR) data, and zonal wind data. In order to investigate the influences of MJO known as the intraseasonal oscillation (30–90 days), analysis of the data was carried out after 10–100 days band-pass filtering. The analysis results show that the intraseasonal oscillation SSHA along the coasts of Sumatra, Java, and Lesser Sunda Islands generally have a spectral peak at 91 days associated with the spectral peak of the MJO, except for Sunda Strait (61 days), southern coast of West Java (55 days), Sawu Sea (58 days), and Ombai Strait (100 days). Further analysis suggests that the MJO phase 3 generates Kelvin waves propagating eastward along the coasts of Sumatra, Java, and Lesser Sunda Islands with phase speed ranging from 2.56 to 3.85 m/s.
Size distribution of Strombus luhuanus Linnaeus, 1758 in Oma coastal waters, Central Maluku, Eastern Indonesia
Authors: Haumahu S , Uneputty Pr A , Lewerissa Y A 
Published: October 2019

Abstract

Strombus luhuanus is a marine mesogastropod known as strawberry conch belongs to the Strombidae family. This species is consumed by the coastal community in Maluku province and collected by people at various shell size. The objective of this research was to determine the temporal size distribution and the size difference between its sexes. Sampling was conducted in Oma coastal water, Central Maluku, Eastern Indonesia. A specimen of S. luhuanus collected randomly during low tide from April to July 2018. Some characters of S. luhuanus were measured including shell length, shell width, spire height, and lip thickness. The result of this research showed that shell length of this species varied between 30.81 mm and 55.20 mm; the shell width varied from 16.33 mm to 32.25 mm; its spire height varied between 5.00 mm and 15.20 mm, while the lip thickness varied from 0.10 mm to 5.54 mm. The average of shell length, shell width and spire height of S. luhuanus were high in June sampling period compared to another sampling periods, whereas lip thickness of this species was high in July sampling. Based on its sex, the shell size parameters measured in our study were higher in female specimen than the male one. The size groups of this gastropods were dominated by 38.79-47.39 mm in shell length. Lip thickness of the shell showed that S. luhuanus was in developing stage of growth in this study and S. luhuanus showed sexual dimorphism.