bluuebunny/crossref_metadata_2025 huggingface dataset:
CFD simulation of turbulent flow behaviour in a mixing reactor with Rushton impeller
Authors: Sharan V , Rohit K , Ravishankar M , Bhuvaneshwar D , Harish R
Published: January 2021

As in the current industrial process, mixing is an essential process for various streams of application in engineering fields. The aim of this paper is to predict flow behaviour of the mixing process in mixing tank with the Rushton impeller and find out the best suitable design that creates required turbulence for producing a better degree of homogeneity in mixing. The rotation of the impeller is modelled using MRF in a single-phase medium treating the walls with a no-slip boundary. The mixing characteristics of single and multiple impellers are investigated by varying the impeller speeds and the results of velocity and pressure contours are compared to identify the best impeller with enhanced mixing.
Turbulent thermal characteristics and air flow patterns in a naturally ventilated tunnel with roof openings
Authors: Mason Ashley A. , Harish R.
Published: January 2021

Air flow is a major characteristic in the tunnel ventilation design, to avoid severe disasters like smoke suffocation problems in tunnel and fire accidents. Tunnels are best ways to reduce distance between two adjacent places. It may be underground or above ground, depending upon the usage of it. There are different types of tunnel ventilation, e.g. roof vents, side vents, mechanical ventilation, naturally ventilated etc. This paper majorly focuses on roof vents mass extraction with different sizes of the heat sources and it also records the horizontal and normal velocity for different sizes of heat sources. The Reynolds Number is low but still turbulence occurs when we deal with buoyant smoke keeping density as incompressible ideal gas. Ratio of height by width is taken into account and the transient air flow is simulated for 10 seconds, and mass flow is recorded at each time step of 0.1 seconds using Large Eddy turbulence Model to capture the flow physics. It is observed that with changing the heat source size, mass flow rate from each vent changes significantly and it drastically affects the air flow patterns and heat transfer characteristics inside the tunnel.
Product defect categorization using machine vision through machine learning
Authors: Karthikeyan G , Naveen Monagari , Jegadeeshwaran R , Sakthivel G , Saravanakumar D , Lakshmipathi J
Published: January 2021

O-rings are among the seals most often used in the industry. O-rings accuracy measurement and inspection play a significant role in seal quality control. Human tests can be unpredictable and can take time. The goal of this paper is to use detection algorithms based on machine vision technology to monitor the O-rings norm, which also has the correct measurement rule and the classification rule. During this, we find an entirely different variety of good defects, Material shortage, Bounce, Spiral, and Breakage. Extract values for the elements by using MATLAB. Feature selection optimization attribute choice with MATLAB and classification exploitation of KNN, SVM, call Trees and alternative classifier variety with MATLAB is performed to check for the utmost prediction precision. To evaluate the recorded images of O-rings and conduct the measurement and inspection processes a computer vision program is applied. Then the GUI system is built to interface the user with the credibility of accessing the trained model. The proposed GUI is tested via a sequence of O-rings being checked.
Modelling and Control of Air Bellow based Active Suspension System
Authors: Muthukumar M , Arjun S V , Saravanakumar D , Sakthivel G , Jegadeeshwaran R
Published: January 2021

This paper presents a complete design and simulation of active suspension actuated using pneumatic air bellow. The electronic controlled active suspension will control all vertical force acting from road surface by regulating the air mass of bellow. Quarter car active suspension is modelled and analysed using Matlab-Simulink. The output of designed active suspension system is simulated under standard road input that gives the response of the suspension to varied roughness of road surface. From the results it is evident that proposed active suspension system can suppress more than 60% than standard passive suspension system.
Role of programmatic advertising on effective digital promotion strategy: A conceptual framework
Authors: Uday Kiran K , Arumugam Thangaraja
Published: January 2021

Today“s world of digital advances technology has created major impact on the effective, efficiency and increase performance to companies with improved information and create more connective with customers and clients, and also streamline the process of various activities. As today advertising spending has involved in more of applicable and dependable, automation process of digital ads selling along with its effective campaigning implementation has an important role in supporting to the online marketing this growth is known as “programmatic Advertising.” The programmatic advertising as converted the traditional method of execution of ads which are involved in the ad stock field has normally used by company“s publicity. The digital automation advertising has been very important tool which creates efficient and effective than manual process. The earlier pattern of advertising observation process as seen gradually decline in the advertising promotion method and also has brought less margin with more cost for the ad companies in the field of advertisement which has forced the companies to adopt the innovative technology and systems for the competitive world. This paper describes the theoretical and conceptual framework of programmatic advertising and explores how the programmatic advertising as an important tool will help the advertisers and ad agencies in developing effective digital promotion strategies.
UVM methodology based functional Verification of SPI Protocol
Authors: Kulkarni Aman , Sakthivel S M
Published: January 2021

The scalability and complexity nature of the integrated circuit design makes the verification process more complicated and time-consuming. Therefore, in the present modern-day SOC’s there is a strong need for verification architectures with increased reusability and easy accessibility. The UVM methodology-based verification architecture with reusable components is one of the widely accepted test bench architectures for carrying out such functional verification. This paper presents a UVM methodology based functional verification of the SPI protocol core with a dedicated architecture. First the SPI core is modeled using Verilog RTL. Then using the reusable components in UVM + System Verilog environment, the SPI core is verified under two modes such as i) SPI communication with wishbone interface and ii) SPI Master-Slave communication.
Design of Low Power SRAM Cell Using Adiabatic Logic
Authors: Penugonda Ramya sri , Ravi V
Published: January 2021

In VLSI system design power consumption and energy dissipation are become more important. To optimize the power consumption we are using adiabatic logic which is having capability of reusing power. In this paper we proposed novel 7T SRAM cell using MCPL adiabatic logic. We compared the performance of energy dissipation and power consumption of conventional 7T SRAM and adiabatic SRAM. Furthermore, the conventional 6T,7T SRAM cell and the designs which are related are designed using FINFET devices to achieve low power.7T SRAM is more stable compared to 6T SRAM but due to excess transistor in 7T SRAM the power consumption will be more. SRAM cells are designed in cadence EDA environment and layouts for these circuits are carried out in cadence Assura tool.
Energy Efficient Adiabatic Logic Circuit for Improve Security in DPA Resistant RFID
Authors: Vaishiba A G , Durai Dr. Ananiah
Published: January 2021

A Differential Power Analysis (DPA) attack is an exploit which overcomes the hardware and software security by analyzing the correlation between electricity usage of a chip in a device and the encryption key. These attacks are non-invasive, leading an intruder to crack a system without leaving any trace. CMOS Technology is prone to DPA attack because of higher power dissipation. A DPA resistant adiabatic technique has been analyzed which has lower power dissipation when compared to the CMOS technology. The conventional Positive Feedback Adiabatic Logic (PFAL) suffers from certain non-adiabatic energy loss. Hence, Energy Efficient Secure Positive Feedback Adiabatic Logic (EE-SPFAL) is proposed which reduces the non-uniform power consumption, preventing information leakage thus securing the system from DPA attacks. Thus the proposed EE-SPFAL is used to design logical circuits such as buffer, OR-XNOR and AND-NAND gate. It is proved that the information leakage in the form of current consumption takes place in PFAL buffer whereas current consumption traces in EE-SPFAL circuits are uniform, depicting the ability of the proposed logic family to resist DPA attack. The simulation was done using Cadence virtuoso 180 nm technologies.
Blast Fragmentation Analysis using Image Processing
Authors: Kumar Ujjwal , Shaik Ayesha
Published: January 2021

This paper proposes an image enhancement algorithm for rock particle images during blast fragmentation. Image enhancement of rock piles plays an important role in rock size distribution. To measure the rock size, the original images are not of good quality. So our method is used to enhance the image to help the rock size distribution. The proposed method is implemented in Matlab software.
An Innovative Approach for Secured Smart Office and Home System using IoT
Authors: Shashank Apurva , Vincent Rajiv
Published: January 2021

As technology grows every day, everybody wants to use smart devices (phones, lights, appliances, etc.). Nowadays we find that many houses and offices are neither safe nor smart. To overcome this problem, we have proposed a smart and secure office and home system using IoT. The proposed system contains several components, where a single microcontroller will connect and control several components. Our system will sense the environment and will detect movement and also will distinguish whether a human has moved in or out of the sensors. Secondly, when light falls on its resistance decreases and as it senses darkness its resistance becomes high. Next, our system will sense the blockage level in the housing pipelines and give information about the exact blockage point. Finally, it will control the gardening system. This system will monitor and use all the data from the sensors and principally facilitate physically challenged persons to manage all of their home and office devices from one place, and simultaneously saves power as well.
The influence of Ag in TiO2/NGP composites as a high performance photocatalyst under UV and visible light irradiation
Authors: Fauzian M , Taufik A , Saleh R
Published: January 2021

Ag/TiO2 nanocomposites were synthesized using a sol-gel method, and Ag/TiO2/NGP composites were synthesized using a co-precipitation method. X-ray diffraction (XRD), UV-Vis absorbance, Raman spectometry, and thermogravimetric analysis (TGA) were used for the characterization of prepared samples. The photocatalytic performance of all prepared samples was tested by removing methylene blue (MB) dyes. Photocatalytic activity using UV and visible light irradiation. The photocatalytic performance of all Ag/TiO2/NGP composites was much higher than pure TiO2 and TiO2/NGP composites. The enhanced photocatalytic ability is predominantly due to the properties of NGP and the surface plasmon resonance (SPR) of Ag nanoparticles (NP). The NGP acted as an electron transporter and acceptor in composites and inhibited electron–hole recombination. The Ag NPs acted as an electron trap, making the separation of photo-generated electron–hole pairs easier. The best condition for the photocatalytic activity of Ag/TiO2/NGP composites was pH 13. Holes were the major radicals involved in the photocatalytic process of Ag/TiO2/NGP composites.
The parameter estimation of logistic regression with maximum likelihood method and score function modification
Authors: Febrianti R , Widyaningsih Y , Soemartojo S
Published: January 2021

The maximum likelihood parameter estimation method with Newton Raphson iteration is used in general to estimate the parameters of the logistic regression model. Parameter estimation using the maximum likelihood method cannot be used if the sample size and proportion of successful events are small, since the iteration process will not yield a convergent result. Therefore, the maximum likelihood method cannot be used to estimate the parameters. One way to resolve this un-convergence problem is using the score function modification. This modification is used to obtain the parameters estimate of logistic regression model. An example of parameter estimation, using maximum likelihood method with small sample size and proportion of successful events equals 0.1, showed that the iteration process is not convergent. This non-convergence can be solved with modifications on a score function. Modification on score function is to change a score function, a matrix of the first derivative of the log likelihood function, to the first derivative matrix itself minus multiplication of information matrix and biased vector. The modification of the score function can quickly yield values of parameter estimates, especially when the sample sizes are larger, and convergence was reached before the 10th iteration.
The accuracy of transfer learning using neural network method for sentiment analysis problem on Indonesian tweets
Authors: Augustizhafira A N , Murfi H , Ardaneswari G
Published: January 2021

In this paper, sentiment analysis is applied to one social media called Twitter. Sentiment analysis is categorized as a classification problem that can be solved using one of machine learning methods, namely Neural Network. If machine learning is applied, it is necessary to rebuilt the model from scratch using new training data that requires manual labelling process. Hence, it is better to apply other learning besides machine learning, such as transfer learning. The simulation in this research yielded an accuracy of transfer learning using Neural Network which will be tested by N-grams (bigram and trigram) feature and one of feature selection method, namely Extra-Trees Classifier. The highest value of transfer learning accuracy is obtained when one hidden layer, 250 neurons on hidden layer, and tanh activation function are used. The use of feature selection method in simulation can also improve the transfer learning performance, so that the accuracy value is higher than the one that does not use feature selection method.
Model of transmission of three types Leprosy Disease with treatment
Authors: Martahi R L , Tasman H
Published: January 2021

Leprosy disease is caused by infection of Mycobacterium leprae that affects the skin and nerve. The treatment duration for leprosy takes 6 to 24 months with multi-drug therapy. In this article, a 6-d mathematical model for transmission of three types leprosy disease with treatment was constructed. Analysis and numerical simulation were done to explore the existence and stability of equilibrium points and basic reproduction number R0. The local stability of endemic equilibrium point was done by numerical simulation. Numerical simulation also confirmed that the disease-free equilibrium is locally asymptotically stable when R0 < 1 and the endemic equilibrium point locally asymptotically stable when R0 > 1. Numerical simulation was also done to show the sensitivity of R0 with respect to some contact parameters. The result showed that the change of contact rate between susceptible people and lepromatous type infected hosts has more effect to change the value of R0. The reduction of contact rate between susceptible people and lepromatous type infected hosts is more effective to control prevention leprosy disease compared with tuberculoid and borderline types.
Classification of the likelihood of Indonesian Facebook users in spreading hoaxes using Support Vector Machine (SVM)
Authors: Rampisela T V , Andarlia H T , Rustam Z
Published: January 2021

Social media is the most commonly accessed internet content by Indonesian netizens; 97.4 % Indonesians access social media while using the internet. In 2016, Facebook was the most commonly used social media format for Indonesian internet users. While many are benefited by the features offered by Facebook, many also use Facebook for things that they are not supposed to, such as sharing hoaxes, either intentionally or unintentionally. This clearly puts Facebook users at a disadvantage, considering the increasing trend of hoax-sharing nowadays. Therefore, this research aims to prevent the spread of hoax through Facebook by analyzing the pattern of how people use Facebook. This pattern is obtained from a survey on 200 samples that use Facebook, chosen by purposive sampling. Using the Support Vector Machine method, an application of the collaboration between mathematics and computer science, the acquired data is used to predict whether or not someone has the potential of spreading hoaxes. Simulation results show that the average of the prediction accuracy of this binary classification problem is 86 percent. Hence, it is hoped that Facebook could prevent the sharing of hoaxes by making use of the results from this research.
Analysis of factors that affect the empathy level of mathematics FMIPA UI students
Authors: Syarif M A , Setiadi R , Soemartojo S M
Published: January 2021

Mathematics students of FMIPA UI are required to have responsibility in behaving accordance to the society norms, highly intellectual, set a good example to the society, and have a high sense of empathy. Empathy causes students have feeling, understanding, and caring for others. Therefore, empathy has to be developed. Empathy has four dimensions namely perspective taking, fantasy, empathic concern, and personal distress. The purpose of this study is finding factors that affect the empathy level of Mathematics FMIPA UI students. If the factors can be found, so the empathy level can be increased. Population in this research is Mathematics FMIPA UI students in generation of 2012–2016 with active status of academic year 2017/2018. The number of all students is 513 people. The data were collected by distributing questionnaires to 170 mathematics students of FMIPA UI who have been selected as sample. The sampling method used here is Simple Random Sampling (SRS). The main method that is used in this study is Partial Least Square (PLS). From the data analysis, it is found that the factor that give most affect on Mathematics FMIPA UI students’ empathy level is fantasy. Other factors that also affect empathy level of Mathematics FMIPA UI students are perspective taking, empathic concern, personal distress, parenting patterns, and gender.
Varying intercept regression model
Authors: Rosalia  , Abdullah S , Nurrohmah S
Published: January 2021

Varying intercept model is a regression model that is applied to nested data, which consists of several groups and each group contains several individual observations. Several characteristics are often found in nested data, namely, the variance between groups and individual observations from the same group are correlated. By considering errors in two different levels, the individual and group levels, the varying intercept model is more suitable than the linear regression model in nested data because varying intercept model accommodates those characteristics. In this thesis, we discussed the varying intercept model both with and without a predictor variable. The varying intercept model consists of several parameters that must be estimated, namely, regression coefficients and variance components. There is also a random effect, which is a group effect and also a random variable. The regression coefficients are estimated using Generalized Least Squares (GLS) and Maximum Likelihood (ML) via the Expectation-Maximization (EM) algorithm. The random effect in varying intercept model is predicted using Best Linear Unbiased Prediction (BLUP). On the other side, the variance components in varying intercept model are estimated using Maximum Likelihood via Expectation-Maximization (EM) Algorithm. In this thesis, we used a simulation to analyze the effect of the standard deviation of the error components in the varying intercept model and the effect of the number of individual observations in each group toward the standard deviation of the error components. The simulation results show that if the standard deviation of the error component in the individual level is greater than the standard deviation of the error component in the group level, then the classifications of individual observations into several groups should be ignored. On the other hand, if the standard deviation of the error component in the individual level is not greater than the standard deviation of the error component in the group level, then the classifications of individual observations into several groups should not be ignored. The simulation results also show that the number of individual observations in each group is not associated with the standard deviation of the error components.
The GSp criterion on subset selection method for regression in the presence of outliers and multicollinearity
Authors: Nabila A , Widyaningsih Y , Nurrohmah S
Published: January 2021

Linear regression models a relation between a response variable with regressor variables and produce regression model. Ordinary least squares (OLS) method is often utilized to estimate parameters of linear regression model. OLS method will produce the best linear unbiased estimates when all the assumptions are met. The “best” means the estimate is unbiased and has the minimum variance. However, in real data, those assumptions are often violated, such as the multicollinearity and outliers. Multicollinearity will produce a large variance of the regression parameters, while outliers will cause a biased estimate. Jackknife ridge M-estimator is recommended to be implemented in the model when these problems are present. Jackknife ridge M-estimator is a parameter estimation method of the regression with robust property, which makes robust to outliers, and ridge method is utilized to overcome multicollinearity. Whereas the jackknife method is utilized to reduce the bias from the result of the ridge method. In multiple linear regression, regression model could possibly contain many candidates for regressor variables. Subset selection method is utilized to select some of those regressors that best predicts the response variable. The selection criterion that can be utilized on the subset selection method when outlier and multicollinearity are present is the GSp criterion. The reason for this is because the GSp criterion is based on jackknife ridge M-estimator, which is able to solve the problem of outlier and multicollinearity. Furthermore, GSp criterion is implemented to obtain the best model on predicting IQ based on several predictors. It was found that IQ could be predicted by only doing 3 personality test which is test 1, test 3 and test 5 instead of all 5 different personality test.
Linear regression model as an approach to analyze spatio temporal data to know the influence factors of the number of crimes in North Sumatera
Authors: Manurung E N , Widyaningsih Y , Aminah S
Published: January 2021

Crimes in Indonesia tend to increase every year, both in variation and in number. Crimes in this study include murder, torture, rape, theft, fraud, and other cases that make people feel insecure. This study aims to know what factors affect the number of criminal acts in the Province of North Sumatera and determine the influence of time and location in 33 districts/cities in North Sumatra. This study uses secondary data collected by POLRI, BPS, and Dinsos in North Sumatera Province in 2013, 2014, 2015 and 2016. The independent variables used are the number of unemployed people (X1), the number of poor people (X2), population density (X3), human development index (X4), the number of places of worship (X5), the economic growth rate (X6) and the number of families with a social psychological problem (X7). The linear regression model is used as an approach to analyze. The results of this study show that the independent variables significantly influence the number of crimes acts in North Sumatera Province. The independent variables are unemployment (X1), the number of poor (X2), population density (X3), and human development index (X4). There is a significant location influence on the occurrence of the number of criminal acts in 33 districts/cities of North Sumatera Province. Based on the descriptive statistics, Sibolga, Tebing Tinggi, Padangsidempuan, Tanjungbalai, Samosir, and Gunungsitoli are the six districts with the highest proportions in criminal actions, where those districts are all cities.
Discrete Weibull-geometric distribution
Authors: Mabel Y O , Novita M , Nurrohmah S
Published: January 2021

The failure-time distribution is used to describe the life of a device, material, or structure. One of the most commonly used distributions to analyze failure-time data is Weibull distribution. The Weibull distribution is very flexible for modeling varying types of failure rates data with constant, increasing and decreasing shapes, but cannot be used for modeling data with unimodal failure rates. Because of this, we developed the Weibull distribution using compounding method to produce a Weibull-Geometric distribution. The Weibull-Geometric distribution is useful for modeling failure rates data with a unimodal shape. In studies of failure, time to failure is frequently measured in the number of cycles to failure or shocks to failure and become a discrete random variable. Hence, this paper discusses the formation of distribution that more appropriate to modeling discrete failure data. The discrete distribution is obtained by discretizing the continuous Weibull-Geometric distribution. The discretization is carried out by maintaining one of characteristics of the continuous distribution, that is, its survival function. The result distribution, called Discrete Weibull-Geometric distribution (DWG) has unimodal failure rates, right skew, and more appropriate at modeling discrete failure data. At the end of this paper, the Discrete Weibull-Geometric distribution is used to illustrate the real dataset and show that DWG distribution is the appropriate model.
The community structure of epiphytons on Utricularia sp. and Hydrilla sp. plants at Situ Alam FMIPA Universitas Indonesia, Depok, West Java
Authors: Zuardi S H , Wardhana W
Published: January 2021

Water plants will affect abundance and diversity of epiphytons in the community structure. The purpose of this research is to know the difference between the community structure of epiphytons on Utricularia sp. and Hydrilla sp., also periphytic planktons at Situ Alam FMIPA UI. Abundance and diversity of epiphytons community are the main discussion in this research. Research was carried out from March 2018 until May 2018. Using the purposive sampling method, samples were taken from Utricularia sp. and Hydrilla sp. Each sample was taken three times, one repetition, once every 2 weeks. Research showed that 67 genera, including 1 planktonic genus were found on the object glass. Utricularia sp. had higher abundance of epiphytons (84609 cells/mL) than Hydrilla sp. (74392 cells/mL). Both diversity indices are categorized as low diversity (H’ < 2.302). Different diversities were found between epiphytons on both plants (P < 0.05), but there was no difference between abundance of epiphytons on both plants (P > 0.05).
Comparative morphological analysis of ovaries in Hibiscus rosa-sinensis L. single pink, crested peach and double orange flowers
Authors: Rostina I , Kusumawati S A , Salamah A
Published: January 2021

Hibiscus rosa-sinensis L. generally has a 5-loculed ovary, with each locule consist of numerous ovules. Observations have been made on the ovarian morphology of H. rosa-sinensis L. single pink, crested peach, and double orange flowers. The specimens of ovaries were prepared by a free-hand section technique and observed under the Dino-Lite digital microscope. The results show that a single pink flower has a normal ovary that consists of 5 locules. There are two ovule rows in each locule, with each row consists of 6 ovules. The observation of the ovaries of the crested peach flowers shows that one locule with another is indistinguishable, but the ovules are still present. Even though ovule still exists in ovarium, the number and the arrangement of the ovules are difficult to determine. In the longitudinal and cross-sections of the double-orange variation, ovules are not found in the ovary. Instead, petal-like structures seem to replace the ovule position. Based on the results of morphological observations, homeosis events are suspected to occur in the ovaries of crested peach and double orange flowers. Presumably, there is a difference in class C genes AGAMOUS expression of the three types. The obtained morphological data is the basis for further research on the molecular analysis of the three variations of the flower.
The utilization of water hyacinth (Eichhornia crassipes) for the development of sludge worm (Tubifex sp.) cultivation
Authors: Ikhsan C , Safitri S D , Khaerunnisa S , Purwanti D , Lestari R
Published: January 2021

Sludge worms (Tubifex sp.) is one of the important components of fish cultures. Sludge worms contain high protein as nutrition for fish foods. The worm grows fast and relatively smaller size that is suitable with the small size of the fish mouth. Intensification of sludge worm production through cultivation needs to be done in order to meet the growing needs of fish food. Water hyacinth (Eichhornia crassipes) is a weed that lends the ecosystem and is not utilized in the community. In fact, water hyacinth has a high protein content to become feed nutrition. This research supports the conversion of water hyacinth into optimal cultivation media. is the experimental design used four media variations namely treatment-I, treatment-II and treatment-III. Fermentation was used to breakdown the fibre of water hyacinth. The water system used a recirculation system. The parameters tested are water quality, water flow rate & dissolved oxygen. The pH showed range from 7.0–7.6. DO showed range from 1.2−1.4 mg/L. The temperature showed range 25.6–28.2 °C.
Isolation, screening, and molecular identification of lignin-degrading fungi isolates from Cibinong Science Centre, Indonesia Institute of Sciences, Cibinong, West Java
Authors: Putri P I P A , Mangunwardoyo W , Sudiana I M , Idris  , Ramadhani I
Published: January 2021

Lignin is a recalcitrant compound that has potential as fuels and chemicals on industries. Contamination of recalcitrant compound with the lignin-like structure on the ecosystem is being concerned worldwide. Fungi is the most targeted organisms with lignin-degrading ability, can secrets laccase and peroxidase to facilitate free radical chain reaction on lignin complex structure. Isolation, screening and identification for isolate with ligninolytic ability is the main purpose of this project. Phylum Ascomycota and Basidiomycota be the main target of this research. Isolation technics that being used are surface sterilization with distilled water and NaClO on PDA medium. Pure culture with ability to grow on lignin minimal medium with black liquor as the only carbon sources then are identified by molecular identification. Isolates that can grow on lignin minimal medium are identified as Fusarium verticillioides strain CBS 127178, Lasiodiplodia sp. LAS-2016 strain CBS 125262, Trichoderma harzianum strain 35814DRJ, and Lasiodiplodia theobromae strain CBS 127106. Four isolates obtained with lignin-degrading ability then preserved by cryopreservation technic for use in the next projects.
Distribution and area changes of mangroves with remote sensing technology in Perancak Estuary, Jembrana, Bali
Authors: Asmara T M , Saraswati R , Hernina R
Published: January 2021

Mangrove vegetation has an important role for its functions and benefits to the coastal area and the society which lives in it. The purpose of this research is to know the distribution and the changes of mangrove vegetation area located in Perancak Estuary area within 10 years, and to know the green-ness level and the environmental parameters of mangrove vegetation; salinity and substrate condition. To observe the distribution and the changes of mangrove vegetation area, supervised classification is used on SPOT satellite imagery in 2007 and 2017. The result shows that the expansion of mangrove vegetation area in Perancak Estuary is 18.7 hectares along with the increasing of the green-ness level. In addition, the environmental parameters which are the salinity and the substrate conditions are also observed, where the average salinity value is 31.54 ppt and the substrate conditions are good (not much waste).
The relationship of volcanic facies and temperature range derived from the associated clay mineral in Gunung Endut, Banten
Authors: Primayudha F , Sahdarani D N , Kadja G T M , Supriyanto
Published: January 2021

Gunung Endut located in Lebak, Banten is one of the prospected areas of geothermal energy resource on the island of Java, Indonesia. The presence of clay mineral in the surface can help to determine the hydrothermal fluid temperature circulating in Gunung Endut. Based on the collected samples, petrography analysis revealed the presence of clay minerals while diffraction method confirmed the presence of dickite, montmorillonite, kaolinite, pyrophyllite, chlorite, diaspore and illite. There are three different temperature range from each volcanic facies. It is predicted that clay minerals at their temperature range in Gunung Endut are formed based on the type of rocks and the topography of the research area.
Spatial pattern of supporting facilities in mangrove ecotourism Karawang regency, West Java
Authors: Angelika P , Handayani T , Susilowati M H D
Published: January 2021

Karawang regency has the second area of mangrove forest in West Java Province with an area of 10.005.93 Ha, which encourages the formation of mangrove ecotourism in Karawang regency. Tangkolak mangrove ecotourism, Cilamaya Wetan district and Pasir Putih mangrove ecotourism, Cilamaya Kulon district is ecotourism that developed in 2018. However, the place has had thousands of visitors, even though it’s classified as a new ecotourism and the facilities that provided are still quite simple. This research purpose is to find out the spatial pattern of supporting facilities based on the interval distance. This study uses a descriptive spatial analysis method. The result is the distance interval affects the formation of facilities patterns around ecotourism. The spatial pattern of these supporting facilities also affects the amount of income and the development purpose, where the facilities that located in close range will have a greater income than intermediate and long-distance intervals as well as the purpose of approaching tourist attractions.
Mineralogy of travertine deposit in Ciseeng geothermal field, Parung, West Java, Indonesia
Authors: Kurniadi D T , Sahdarani D N , Ponka M A , Yoga D A , Sihombing F M H , Supriyanto
Published: January 2021

Travertine deposits are carbonate rocks consists mainly of calcium carbonate minerals, supersaturated from bicarbonate-rich water. Both recent and fossil travertine deposits are found in Ciseeng geothermal field, West Java. The travertine deposits are distributed around three distinctive areas Tirta Sayaga, Mount Panjang and Mount Peyek. This study aims to determine minerals found in travertine deposits in Ciseeng geothermal field. Mineralogical analysis can determine the evolution of hydrology system and local climate change. Principal methods of analysis consists of petrographic and diffraction methods. Analysis results indicate similar mineral composition of calcite and microcrystalline carbonate (micrite) between recent and fossil travertine deposit with more diverse texture in fossil travertine due to the evolution of water composition affecting deposition and diagenesis process. The absence of aragonite indicates a low-temperature geothermal system.
Rock physics modelling in unconsolidated sandstone reservoir based on contact theory method case study: FRR Field, Kutai Basin
Authors: Riyanto A , Maulana M R , Syari F T , Widyarta R M
Published: January 2021

The study of rock physics modeling has been successfully carried out in FRR Field, Kutai Basin. This study aims to predict elastic parameters of rock such as V
p, V
s, and density which represent the characteristic of reservoir. The Contact Theory (CT) method was used for conducting rock physics modeling at the unconsolidated reservoir. CT method combines the elastic modulus of Hertz Mindlin at the critical porosity (Φ0) and Hashin Shtrikman Walpole lower bound (HSW−) to interpolate the elastic modulus from the critical porosity to the minerals modulus. Gassman model has been applied to estimate bulk modulus of a fluid-saturated rock with variation water and gas saturation. The data used in this study is log data coming from one well in FRR Field, Kutai Basin. The targeted reservoir was identified as gas sand reservoir that was deposited in the channel complex of turbidity system. Based on the data, the reservoir has the majority of sandstone rock marked by low density and low gamma-ray at the upper part of log data. The results show correlation between elastic properties estimation and log data with the correlation of V
p was 0.66; V
s was 0.5310, and density was 0.99. This result was indicated that the CT method successfully predicts elastic parameter in unconsolidated sandstone reservoir of the FRR Field, Kutai Basin.
The Benktander claim reserving method, combining chain ladder method and Bornhuetter-Ferguson method using optimal credibility
Authors: Triana S , Novita M , Sari S F
Published: January 2021

Based on the settlement period for insurance claim, insurance is divided into 2 types of business which are short-tail business (settlement period <1 year) and long-tail business (settlement period ≥1 year). In long-tail business, it is important for insurance company to have claim reserve in order to settle claims in the future. Claim reserve modelling is done using chain ladder method that is based on the trend of paid claims. Another method that is often used is Bornhuetter-Ferguson which is based on paid claims and also premium. In this paper, Benktander method that combines chain ladder and Bornhuetter-Ferguson using optimal credibility is introduced. Optimal credibility is obtained through minimum mean squared error and minimum variance. Benktander provides moderate reserve compared to chain ladder and Bornhuetter-Ferguson.
Study on European put option pricing with underlying asset zero-coupon bond and interest rate following the Vasicek model with jump
Authors: Lukman P C , Handari B D , Tasman H
Published: January 2021

This paper examines the price of European put options with underlying asset zero-coupon bond and the interest rate that satisfied the Vasicek model with jump. The study was conducted by reconstructing the European put option pricing equation. The jump size is defined following a mixed-exponential distribution. By utilizing infinitesimal generator and martingale concepts, Laplace transform is constructed for the distribution of the Vasicek model with jump. Then, using the results of the Laplace transform for the distribution of the Vasicek model with jump and the concept of equivalent martingale measure, the European put option pricing equation with underlying asset zero-coupon bond is constructed.
Performance evaluation of the Bühlmann credibility approach in predicting mortality rates
Authors: Harjani D A , Nurrohmah S , Novita M
Published: January 2021

Modeling mortality is an important thing for insurance company in determining the appropriate premium for a policy holder. This paper explains the Bühlmann credibility approach for modeling mortality. Bühlmann’s credibility model is generally used to predict the value of a random variable in the next future period. In predicting the value of a random variable in the next two or more future periods, an approach is needed. In this paper, the Bühlmann credibility approach is done through 2 strategies: the expanding window strategy and the moving window strategy. The expanding window strategy is done by adding the predicted value to the data to produce a predicted value in the following year while the moving window strategy is done by adding the predicted value to the data and discarding the oldest data to produce a predicted value in the following year. Mortality prediction performances from the Bühlmann credibility approach are being analysed by comparing the values of AAMAPE and the reduction ratio of the Bühlmann credibility approach to the Lee-Carter model. From this paper, it was found that the Bühlmann credibility approach produced better mortality predictions compared to the Lee-Carter model in case of Australian mortality data.
Recursive and moment-based approximation of aggregate loss distribution
Authors: Ghinawan F , Nurrohmah S , Fithriani I
Published: January 2021

Determining the distribution of aggregate loss is an important issue for insurers. Basically, the distribution of aggregate loss can be determined using n-fold convolution of the probability density function of severity distribution. However, problems in computation for this method causes findings of new methods to approximate aggregate loss distribution. One of the methods which is widely used and claimed to give a good approximation is Panjer recursion. Panjer introduced a recursion formula which can be used to compute aggregate loss probabilities. This method requirements are discrete severities distribution and (a, b, 0) class frequency distribution. The Panjer recursion method could not be applied if those two requirements are not met, so a discretization process is needed for continuous severity cases. This paper explored the use of Panjer recursion method for continuous severity cases. The method of rounding is used to discretize the continuous severity random variable with span h. It means that random variables which are the discretized version of severity random variables have probabilities in the span of h (h, 2h, 3h, and so on). The result improves when the discretization span is small enough. Beside Panjer recursion method, there is a new method, called moment-based, which can be used to approximate aggregate loss distribution using its moments. This method presents an approximation formula of aggregate loss distribution probability density function, which contain coefficients which can be determined by matching its moments with aggregate loss moments. Both of these methods tend to give relatively similar results when the span used in the recursive method is small enough and moments used in moment-based is adequate. The span of discretization for the recursive method is said to be small enough if no jump is seen in cumulative distribution function of severity random variables. t moments used in moment-based is said to be adequate if the result using t + 1 moments give no significant difference.
Claim reserving prediction with Bornhuetter-Ferguson method
Authors: Saputra I G C D , Nurrohmah S , Sari S F
Published: January 2021

In the long-tail business insurance class, claim settlement takes at least one year, since the claim was filed. This is because insurance companies must investigate in advance of the incident. The problem in the long-tail business can be attributed to the large or unresolved number of claims, called outstanding claims. The prediction of outstanding claims has an important role considering insurance companies are required to allocate sufficient reserves for future payment of claims. Generally, the problem of prediction of outstanding claims utilizes run-off triangle. Run-off triangle is an instrument, which is used to analyze the relationship between claims payments that have been made over the past few years. One of the prediction methods that commonly used is the Bornhuetter-Ferguson method. This method will be applied to the paid loss and ALAE Commercial Auto/Truck Liability/Medical insurance data, which is obtained from Highline Annual Statement Schedule P Data from all industry in the United States for the period 1999–2008, where the claim payment is stated in USD (000’s).
The development of biology instructional media based on macromedia flash from the invertebrate’s inventory output at “Pulau Tikus”
Authors: Anggraini N , Jumiarni D , Ekaputri R Z
Published: January 2021

The Purpose of this research is: 1) to know and inventories the types of invertebrates which live is in Tikus Island; 2) to develop the biology instructional media of animal course based on the macromedia flash for the 10th grade of high school students, 3) to study the quality of learning based media through the invertebrate’s macromedia, and its assessment on biology teachers. The object of this study utilizes the invertebrate inventory at Tikus island, in which practical survey, interview and explorative descriptive on another types of biota was conducted at Tikus island. The development of product learning was based on macromedia flash research (Research and Development), by implementing the ADDIE Model (Analysis, Design, Development and Production, Implementation, Evaluation). According to the obtained results, there were 18 Species taken from 6 phylum invertebrates. These are Porifera, Coelenterate, Mollusca, Vermes, Echinoderms and Arthropods. The survey showed that based on the validation of linguistic expert (86,4%), validation subject matter experts (83,9 %), validation of media expert (87,8%) the validator eligibility by teachers (84,5%) and the test of the students (86,04%) are all in very good criteria. As seen at the percentage range, it can be inferred that biology media based on macromedia flash of the invertebrate inventory at Tikus island is deemed as very appropriately used by the teachers and students.
The analysis of students’ interest and their learning outcomes through the implementation of Course Review Horay (CRH) method
Authors: Ekaputri R Z , Primairyani A , Karyadi B , Parlindungan D
Published: January 2021

This study aims at investigating whether the implementation of “course system horay” is able to boost the students’ outcome and their interest in the subject of general biology, the odd semester of the 2019/2020 academic year. The type of this study is categorized as classroom action research with 50 students as the subject research. The data collection was conducted using observation, questionnaires, paper-based tests, and documentation. Meanwhile, the technique of analysis was done using descriptive study. By implementing the course system horay, we report that there is a significant increase in the students’ outcome in the general biology course. The analysis also reveals that the mean scores of students’ interest are higher on average.