bluuebunny/crossref_metadata_2025_split huggingface dataset:
Claim reserve prediction using the credibility theory for the Chain Ladder method
Authors: Karmila S , Nurrohmah S , Sari S F 
Published: January 2020

Abstract
A claim reserve is a reserve that must be prepared by a long-tail business insurance company to fulfil its obligations to future policyholders. One of the most popular methods for predicting claim reserves is the Chain Ladder method. However, on the Chain Ladder method, the claim reserve is predicted solely based on individual information (information derived from the company’s past experienced). If the individual information is not enough, an actuary needs to consider other information that is collective information (market experience). Both information can be combined by applying Bühlmann-Straub credibility theory. This paper will discuss about implementation of credibility theory for the Chain Ladder method to predict claim reserve for the data of private passenger autoliability/medical insurance in 1998-2007 are published by National Association of Insurance Commissioners (NAIC).
Intrusion detection system model using Fuzzy Kernel C-Means and Laplacian Score feature selection
Authors: Rustam Z , Maharani J 
Published: January 2020

Abstract
Nowadays, where the technology dominates every field and activity like transaction, learning activities, private or corporate data storage, and so on are things that we have to look in detail especially in terms of security both in data storage and technology utilization. The trust of the security itself can be represented by the accuracy on model we used but the question is “Which model is good for the security?”, that question can be answered by the research or trial of models either by combining the models or construct the new one. Therefore, in this paper we tried an intrusion detection system model by combining Fuzzy Kernel C-Means method as a classifier and Laplacian Score method as a feature selection applied on KDD Cup 99 Data Set. As a result, we will see the comparison of the accuracy of intrusion detection system (IDS) model using Fuzzy Kernel C-means with and without Laplacian Score Feature Selection for the same data and features that resulted 60% and 67.06%, respectively.
The utilization status of Yellowfin Tuna (Thunnus albacares) in Morotai Island Regency
Authors: Talahatu M F , Susiloningtyas D , Budiharsono S , Handayani T 
Published: January 2020

Abstract
Morotai Island Regency is located in the adjacent of three National Fisheries Management Area of Indonesian Republic (WPPNRI 715, WPPNRI 716, WPPNRI 717). Geographically Morotai Island’s waters lie in two Indonesian hydro-oceanography phenomenon, namely Throughflow and Eddy Halmahera which affect the abundance of marine resources. This study aims to determine the utilization status of Yellowfin Tuna (Thunnus albacares) in Morotai Island regency including: catch per unit effort (CPUE), maximum sustainable yield (MSY), total allowed catch (TAC) and Utilization rate. Within a period of ten years (2009-2018) Yellowfin productivity was fluctuating with a CPUE of 4.1 kg/trip. Fox surplus production model calculation showed that MSY of yellowfin resource was amounted of 8,657,679 kg/year with a maximum effort value of 42,429 trips/year. The number of TAC value was amounted of 6,926,143 with a utilization level of 12.23%. Yellowfin utilization level was amounted of less than 33.3% which is relatively low. This shows that Yellowfin Tuna stock in Morotai Island regency has not been optimally utilized.
Numerical modeling of abrasion hazard in Senindara River, Bintuni Bay
Authors: Hernawan U , Prasetio F B , Risdianto R K 
Published: January 2020

Abstract
The Senindara River area, which is part of Bintuni Bay, was influenced by the dynamics of the seawater and widely used to support community and industries activities. Alluvium land conditions and partially cliff were potential to abrasion. The research location was Senindara River with focused in Maga River area. This study aims was to obtain potential abrasion hazard of the study area. Numerical modelling was used to analysed the data. Tidal observations were carried out for 15 days with peilschaal and processed using Admiralty method. Current measurements were conducted for 26 hours using the Eulerian method. Modeling using MIKE21 FM Model with momentum, temperature, and density equations. Spatial discretion of the equation was done using the cell-centered finite volume method. Model calibration was done by comparing the output of the model (current and water level) with the observation results. The study shows the value of the basic shear stress of the average model value was greater than the value of the basic shear stress critical model erosion 0.1 N/m2. This shows that at the observation location has a high risk abrasion, especially in the industrial supporting area. Therefore, prevention of abrasion hazards was indispensable.
Rainfall analysis in the Indian Ocean by using 6-States Markov Chain Model
Authors: Miftahuddin  , Maulidawani  , Setiawan I , Ilhamsyah Y , Fadhli  
Published: January 2020

Abstract
In this study, we used Markov chain approach to analyze rainfall dataset from one buoy (4N90E) in the eastern Equatorial Indian Ocean. This study aims to determine the opportunity for transition (displacement) of daily rainfall intensity, where there are six states or conditions of rainfall intensity, i.e. no rain, very weak, weak rain, moderate rain, heavy rain, and very heavy rain. The Markov Chain method used is the Chapman-Kolmogorov equation and the steady state equation. The investigation of the 6-states in Markov chain model show that dynamic probability of transition state for rainfall data is reflexive properties majority. By using the model, it is concluded that the transition rate matrix of the largest transition probability in the area of 4N90E occurs at the transition from state-1 to state-1 as much is 0.72 and state-2 to state-2 is 0.60. The transition probability value becomes 0.5184 and 0.36 for the same state dominant of two periods P
2. The use of the 1st order Markov chain is better than 2nd order.
Study of water discharge in the Ulee Lheue Port Channel, Indonesia
Authors: Setiawan I , Isbah F , Muhammad M , Yuni S M , Purnawan S , Akram A , Ilhamsyah Y 
Published: January 2020

Abstract
Ulee Lheue serve as ferry ports in Banda Aceh, covering an area of ±8 ha. The information on water flow entering the port channel is needed to determine the quantity of water and facilitating transportation at the port. This study includes the measurement of water depth, channel width, current velocity, water discharge, and tides which was conducted every 3 hours at three different water depth. On Jumada I (Jumadil awal) 1-29, 1435 Hijra, the highest and lowest water depth of 6.06 and 3.82 meters occurred in the 23rd and 10th day at 09:00 and 16:00 local time, respectively. The highest and lowest velocity of 0.357 and 0.01 m/s occurred in the 15th and 18th day at 09:00 and 12:00 local time, respectively. The strongest and weakest discharges of 177.93 m3/s and 9.47 m3/s occurred in the 12th and 28th day at 09:00 local time, respectively. The results found a strong correlation between water discharge and current velocity. Thus water discharge and currents play an important role in the channel stability and in controlling sea transportation in terms of scheduling the departures and arrival of ships.
Biodiversity of macroalgae in Pari Island
Authors: Srimariana E S , Kawaroe M , Lestari D F , Setyaningsih WA , Nugraha A H 
Published: January 2020

Abstract
Macroalgae is one of the marine biological resources that have the potential to be utilized further by humans. This research aims to study macroalgae diversity in Pari Island. The study was conducted at two stations using the line transect method at the reef flat area. The results of this study indicate that there are 3 class macroalgae found in Pari Island. 17 species of macroalgae found in the south of Pari Island and 10 species found at the North of Pari Island. Macroalgae species with high abundance are Padina minor and Halimeda opuntia. The highest macroalgae diversity was found at south Pari Island with a diversity value index 2.02.
Assessment of coral reefs health in Nature Recreation Park (TWA=Taman Wisata Alam) Sangiang Island, Banten
Authors: Idris  , Putri A R , Adiwijaya C , Gilang M , Santoso P , Prabowo B , Muhammad F , Andriyani W , Lestari D F , Setyaningsih W A , Zamani N P 
Published: January 2020

Abstract
Sangiang Island had been established as a Nature Recreation Park (TWA) in Indonesia, that requires comprehensive data support for good management. The rise of marine tourism that increased in TWA Sangiang Island behoove to be a concern, especially in coral reef ecosystem. The study aimed to determined the condition of the coral cover and the biomass composition of coral reef fishes, then to identify parameters that affect coral health and the coral reefs health index in TWA Sangiang Island. The observation was carried out in area near to the estuary (Legon Waru), entry point for shipping (Tembuyung), and diving tourism (Legon Bajo). The highest of biomass of target fish was Legon Bajo (0.013 kg / ha) and the lowest was Tembuyung (0.002 kg / ha). Coral reefs health index values in each station varied from 1 (low) to 4 (high). Coral reefs health index in Legon Waru was strongly influenced by live coral cover, and also in Legon Bajo was influenced by live coral cover, rubble and biomass of target fishes, while in Tembuyung was much influenced by fleshy seaweed cover. The results indicated that the coral reef ecosystem on Sangiang Island wasn’t in good condition as a whole.
The potential role of eutrophication, tidal and climatic on the rise of algal bloom phenomenon in Jakarta Bay
Authors: Sidabutar T , Srimariana E S , Wouthuyzen S 
Published: January 2020

Abstract
Over the past several years, a number of algal bloom incidents has been increasingly observed in Jakarta Bay. The increasing frequency of algal bloom incidents, and subsequent environmental impacts are a rising threat to the coastal resources, economy and public health. Eutrophication, tidal and climatic are the three processes that suspected to have a potential role with algal bloom incidences in this bay. To understand the role of these three processes, a monitoring program had been conducted from 2008 until 2015. The study reveals that algal bloom occurrences have a strong relationship with major nutrients ratio. Besides that, the bloom incident occurred particularly after the rainy season to dry season. The tides have a potential role in the spread of bloom formation and stratification. During the study the concentration of phosphate in these waters ranging from 0.01-2.5 μg/L and nitrate 0.01-15.89 μg/L. The ratio of major nutrient (N/P ratio) in this waters ranging from 0.2 - 45.4. The N/P ratio tends to be higher in 2010, where the abundance of phytoplankton raising conspicuously. The N/P ratio may controlling the occurrences of algal bloom, while tidal responsible in bloom distribution, and climatic particularly precipitation, effecting nutrients availability.
Thermal dispersion model of cooling water discharges from industrial activities of steam power plants (PLTU) on the north coast of Paiton, East Java
Authors: Fikri M Y , Atmadipoera A S , Nurjaya I W 
Published: January 2020

Abstract
Necessity electricity in the society especially in industrial activities every year there is an increase in demand. The technology that used in production electricity is one of the Steam Power Plant (PLTU), where Paiton Power Plant is one of the largest power plant in Indonesia and can distribute electricity to Java and Bali. The purpose of this research is to know the process of hot water waste distribution from PLTU Paiton either horizontally or vertically with observation method and numerical model. Tidal model validation with observation data has a high correlation value (r = +0,908). Validation model of hot water waste distribution on surface with observation result has RMSE value equal to (e = 0,96). The observation results show the temperature of the hot water waste in front of the outlet is recorded between 30 °C to 40 °C. Vertically, the distribution of hot water waste near the outlet reaches a depth of 5 m and horizontally the thickness becomes thinner at a distance of about 500 m from the outlet mouth. The model result shows that the distribution of hot water waste distribution occurs more broadly when the low tide.
Monsoonal distribution of phosphate within Tallo Estuary, South of Sulawesi
Authors: Rastina  , Nurjaya I W , Prartono T , Sanusi H 
Published: January 2020

Abstract
Phosphate is one indicator of water fertility and is needed to support the life of organisms, especially phytoplankton. The main source of phosphate in the waters naturally originates from the processes of decomposition, weathering or decomposition of plants and comes from the remains of dead organisms. Besides this phosphates in coastal areas are sourced from rivers that carry waste from land, so phosphates in the river mouth are larger than the surrounding waters. The purpose of this study was to describe the pattern of phosphate distribution in the West and East seasons in the Tallo estuary, Makassar using hydrodynamic and distribution models of pollutants. The results of this study indicate the pattern of spreading phosphate in the study site is strongly influenced by oceanographic conditions of the waters.
Potential of associative bacteria isolates from seagrass ecosystem
Authors: Ismet M S , Jayenti E D , Ismiati P , Utomo R P , Srimariana E S , Hastuti Y P 
Published: January 2020

Abstract
The seagrass ecosystem is rich in organic materials such as nitrates, carbon, and phosphates. Potential nutrient content available in water and sediments influences the presence of an associative bacterial community. This study aimed to explore associative bacteria in seagrass ecosystems which have potentially producing antibacterial activity and cellulase enzymes. Associative bacterial isolation was carried out on sediment samples and seagrass leaves Thalassia hemprichii which was found as the dominant ecosystem compiler. The antibacterial test was carried out using agar diffusion method against Staphylococcus aureus, Pseudomonas aeruginosa, Bacillus subtilis, Escherichia coli, and Vibrio parahaemolyticus. Meanwhile, assay on cellulase activity of the actinomycetes bacteria was using agar diffusion method on CMC media. Isolation of endophytic bacteria of seagrass leaves produced 12 isolates with 2 isolates which could inhibit all targeting bacteria and 3 isolates which could inhibit several targeting bacteria. ANOVA test showed that the sampling location significantly affected the antibacterial activity. Meanwhile, 5 isolates of actinomycetes bacteria were found from the sediments, with 4 isolates having cellulase activity. ANOVA test showed that cellulase activity of the actinobacteria was associated with the density of Cymodocea rotundata and T. hemprichii seagrass species with moderate to high category.
Developing signal processing of echo sounder for measuring acoustic backscatter
Authors: Manik H M , Nishimori Y , Nishiyama Y , Hazama T , Kasai A , Firdaus R , Elson L , Yaodi A 
Published: January 2020

Abstract
The method used to determine the condition of marine biological resources is still conventional, not systematic and not comprehensive. So far, the methods used include divers where the depth of observation is very limited. Another method using sonar for which the acquisition of data is still qualitative. For this reason, it is necessary to strive for new methods that can guarantee careful and accurate observation. This study proposes the detection, classification and quantification of underwater target algorithms using Intelligent Biomass Active Sonar Transducer (IBAST) using a microcontroller unit. IBAST uses acoustic pulses and features that are narrow spectral so as to provide the ability to detect underwater targets (underwater targets) accurately and be able to classify such targets as fish, zooplankton, marine mammals, coral reefs, and other targets. IBAST uses a tracking algorithm and output detector which reduces errors in target detection. The application of the algorithm will be carried out to test the classification method and quantification of underwater targets. This research is very useful in the aspects of quantification of marine life, protection of fishery resources and seabed habitat.
N3-AUV (Nusantara 3-Autonomous Underwater Vehicle): design and implementation for underwater exploration
Authors: Ratnasari Y , Pandewo A F , Santoso S A , Anas D F , Lestari N A , Iqbal M , Jaya I 
Published: January 2020

Abstract
Autonomous Underwater Vehicle (AUV) is a type of underwater robot that can move and perform pre-assigned the missions based on a program which is installed in the microprocessor in the body of the vehicle. AUV uses thrusters to maneuver underwater and may be supported by a compass, various sensors, and a camera that are attached to the vehicle. In this paper, we present the development of N3-AUV and a pool test of this performance. N3-AUV uses 8 thrusters, 2 webcam cameras, Raspberry Pi, a depth sensor, and a compass. The vehicle has a torpedo-like shape so that it is easier to move underwater relatively faster. With 2 webcam cameras, where the first one is placed under the frame to record images of the conditions beneath the vehicle and the second one is placed in front of the frame to record the conditions in front of the vehicle. A pool test was conducted by means of pre-assigning missions, such as navigating pass the goal post, and finding and knocking down an underwater object. N3-AUV can complete three mission of four. Missions that have been carried out successfully are navigation, acquisition, and localization. N3-AUV has a maximum speed of about 1 m/s.
Spatial and temporal variability of geostrophic currents in the Indo-Australian Basin using gridded ARGO Float data
Authors: Saputra J , Gaol J L , Panjaitan J P , Atmadipoera A S 
Published: January 2020

Abstract
Geostrophic current variability in the Indo-Australian Basin (IAB) of eastern Indian Ocean is analyzed by using monthly gridded salinity and temperature data sets (between 2004 and 2016), from CTD ARGO Float. Geostrophic current is derived from dynamic height calculation. We applied time-series EOF analysis by decomposing geostrophic zonal component into dominant variability in several major modes. The variability of geostrophic currents from CTD Argo data analysis had differences, both spatial and temporal variability. There were four major modes, accounting for of 50.47% of the sum explained variance. The anomaly that occurred near the southern coast of Java cannot be detected due to the limited spatial coverage of the ARGO Float distribution. The spatial pattern in the first mode was indicated by positive anomaly at 110°E-114°E and 7°S-13°S. Furthermore, negative anomaly showed in the southern part of the study area. Variability oscillated with annual, semi-annual and inter-annual periodicity. In the second mode, there was a negative anomaly at 10°S-16°S, the rest of area were shown as the positive anomaly. Variability oscillated with semi-annual, annual and interannual periodicity. In the third and fourth mode, they showed variability with the semiannual, annual and inter-annual periodicity.
Waveform re-tracking analyses with Fuzzy Logic on altimetry satellite data in Natuna Waters
Authors: Permana R D , Nababan B , Panjaitan J P 
Published: January 2020

Abstract
Waveform re-tracking analyses have been proven to increase the accuracy of sea surface height (SSH) estimation from satellite altimeters specifically in coastal areas. However, each re-tracking algorithm has its strengths and weaknesses so that no dominant algorithm can be applied to any water condition. The study purpose was to obtain the best SSH estimation from altimeter satellite data using waveform re-tracking analyses with fuzzy logic system. The fuzzy logic system was used to select the best SSH values from the results of waveform re-tracking analyses. The data used in this study were level-2 SGRD data from Jason-2 and Jason-3 in Natuna Waters in 2016-2018. Waveform re-tracking with fuzzy logic system can reduce standard deviation of SSH up to 23.3 cm from the on-board (oceanic) algorithm standard deviation. The highest Improvement Percentage (IMP) value from each observation track was constantly generated by re-tracking with fuzzy logic system up to 70.3%. The result of this study showed that this analysis can produce SSH values with the best accuracy in each track observation.
Implementation of swarm intelligence algorithm on Autonomous Surface Vehicle (ASV)
Authors: Nugroho C A , Vidura A , Rahman M R , Iqbal M , Satria M G A , Jaya I 
Published: January 2020

Abstract
Swarm Intelligence (SI) is an artificial intelligence algorithm related with collective work of individuals intelligence. To date, SI has been developed and installed on autonomous surface vehicle (ASV). ASV use global positioning system (GPS) in determining position, relative orientation to other ASV, and ability to move to desire direction. Aim of this research is to designing ASV and then apply SI algorithm on three ASV to moving simultaneously with preprogrammed formation. These three ASV were divided into two parts, master ASV as a master (order giver) and slave ASV as ASV that follow master ASV. SI algorithm developed using python as its programming language. The formation developed in this research is line and triangle formations. The ASV has 68 x 35 x 20 cm dimension and 0.7 m/s maximum speed. Autonomous system test show that ASV can follow waypoint with 2.3 m and 2.4 m average error at X axis and Y axis and the three-ASV can communicate each other to make formation.
Real-time reef fishes identification using deep learning
Authors: Yusup I M , Iqbal M , Jaya I 
Published: January 2020

Abstract
Reef fishes is an important part in maintaining the balance of various components in the coral reef ecosystem. The existence of reef fish on coral reef ecosystems is a marker of the ecosystem in good condition. Furthermore, it is important to observe the condition of reef fish in a coral reef ecosystem to determine the population and diversity of reef fish in the ecosystem. Observation of reef fish generally by performing a manual visual census by scuba diver. In entering the industrial revolution 4.0 era there is a need to develop technology that is used to monitor the condition of reef fish in a coral reef ecosystem. The development of technology will certainly help researchers, and later on ecosystem manager, in observing the condition of reef fish with automatic identification. The technological development that can be done to observe reef fish is by applying deep learning. In this research we used YOLO deep learning algorithm for automatic identification. YOLO has the advantage of faster object detection. Application of deep learning to identify fish automatically is illustrated using underwater video recording of reef fish.