bluuebunny/crossref_metadata_2025 huggingface dataset:
Carbonated Hydroxyapatite Derived from Cerastoderma edule, Paphia undulata, and Meretrix meretrix Shells
Authors: Wati Rosita , Yusuf Yusril
Published: June 2019

Carbonated hydroxyapatite (CHAp) derived from three different shells, Cerastoderma edule, Paphia undulata, and Meretrix meretrix shells, have been synthesized by precipitation method. Calcium oxide from extracting shells, diammonium hydrogen phosphate, and ammonium bicarbonate was used to synthesis as the starting precursors. The CHAp materials were analyzed by Energy Dispersive Spectroscopy (EDS), Fourier Transform Infrared (FT-IR), and X-Ray Diffractometer (XRD). EDS analysis showed that the Ca/P ratio of CHAp powders were around 1.75-1.77 (bigger than the Ca/P ratio of HAp) and carbonate content of the powder CHAp was 3.10-4.05wt%. XRD data has produced diffraction patterns from the three different shells similar to the apatite structure. The position of the main peak (2θ) diffraction patterns detected at 31.99°, 32.23°, and 31.95°. The lattice parameter of a-axis and c-axis were obtained around 9.37 Å and 6.89 Å. Crystallite size of CHAp samples was 30-40 nm. The FTIR spectra showed that there are functional groups of OH-, PO4
3-, and CO3
2- at wave number around 3447, 571, and 873 cm−1. Based on the results of the analysis, it shows that the CHAp characteristics that had successfully produced from Cerastoderma edule, Paphia undulata, and Meretrix meretrix shells were B-type CHAp.
Samarium Complexes from 2,6-Naphtalenedicarboxylate: Synthesis, Photocatalytic Properties and Degradation of Methylene Blue
Authors: Wulandari Dwi Aprillia , Zulys Agustino , Kusrini Eny
Published: June 2019

Coordination polymer have been attracting considerable attention and present a great potensial in photocatalytic water treatment, paving the way for buliding efficient and enviromentally friendly photocatalysts. In this work, samarium complexes constructed from 2,6-naphtalenedicarboxylate ligand was successfully synthesized using solvothermal methode. Samarium complexes are characterized by Powder X-ray Diffraction (PXRD), Fourier Transform Infrared Spectroscopy (FTIR), Uv-vis Diffuse Reflectance and Cyclic Voltametric. FTIR characterization results indicate peak absence of absorption band arround 1700 cm−1 further confirms that the carboxylate groups in dicarboxylate ligand are completely deprotonated. The value of the band gap obtained from the corresponding transition is 3,1 eV. The LUMO Level reduction potential O2/O2
-* is obtained -2.1 volt, this value is more negative than the potential standard O2/O2
-* reduction is -0,33 volt, so the ability to form O2
-* is greater. Based on the characteristics obtained, this material potential as a semiconductor for photocatalysts methylene blue degradation, where samarium complexes in 240 minutes can degradation methylene blue by 68,6 percent.
Hybrid radial basis function with firefly algorithm and simulated annealing for detection of high cholesterol through iris images
Authors: Anjarsari A , Damayanti A , Pratiwi A B , Winarko E
Published: June 2019

Cholesterol is a lipid (fat) produced by the liver and is required to build and maintain cell membranes. Cholesterol is also important for the metabolism of fat soluble vitamins. This important lipid is found in human blood. Excess cholesterol (high cholesterol) can cause health problems such as being a factor of coronary heart disease that responsible for the heart attacks, liver or kidney disease. Observation of iris pattern can detect several types of diseases, one of which is high cholesterol. The purpose of this research is to detect whether someone is exposed to high cholesterol or not, through iris images based on firefly algorithm, simulated annealing, and radial basis function. Firefly algorithm and simulated annealing are used in the unsupervised learning process in radial basis function neural networks. The stages of high cholesterol detection process are images processing namely grayscale process, thresholding, histogram equalization, segmentation, and detection process is using radial basis function neural network. The percentage success rate of the recognition pattern of iris images for detecting high cholesterol is 89%.
Classification method at acceptance of new student at public university on the national written test
Authors: Antari Ika S W , Zain Ismaini , Suhartono
Published: June 2019

Acceptance of new students at public universities through the national written test is based on the total score and the capacity of the study program. This causes the study program accepts several students who have low scores on the main subject of the study program. The purpose of this study is to find the best method in predicting the probability of being accepted on the national written test and find the minimum score for each subject that must be achieved by participants to be accepted at a public university. There are two classification methods in statistics that are studied to overcome this problem, i.e. logistic regression and random forest. The results showed that the best logistic regression model had an accuracy of 97.11 percent, whereas the random forest method had an accuracy of 96.59 percent. Furthermore, the minimum score for each subject was developed based on the univariate logistic regression model.
Glaucoma Identification on Fundus Retinal Images Using Statistical Modelling Approach
Authors: Anwar A. E. , Chamidah N.
Published: June 2019

Glaucoma is an eye disease characterized by progressive deterioration of the optic nerve head and a broad view that can cause blindness. The Population Based Survey in 2010 indicates that glaucoma was the second leading cause of blindness after cataracts, which was about 8% of 36 million sufferers of blindness worldwide. Symptoms of glaucoma that arise usually cannot be felt directly. So it is necessary to do an eye examination to find out glaucoma, one of which is to look at the size of the optic disk in the digital fundus photo. The previous studies about glaucoma identification were done by using mathematical computation approach that have still not satisfied. Therefore, in this study we propose a new method, i.e., statistical modelling approach to identify glaucoma. In statistical modelling, there are two approaches, i.e., parametrical approach, and non-parametrical approach based on penalized spline estimator. The result of classification accuracy by using parametrical and non-parametrical approaches are 73.3% and 93.33%, respectively. Based on the result, we conclude that non-parametrical approach has better outcome so that it can be used to identify glaucoma on fundus retinal image.
Parameter Estimation of Locally Compensated Ridge-Geographically Weighted Regression Model
Authors: Fadliana Alfi , Pramoedyo Henny , Fitriani Rahma
Published: June 2019

Geographically weighted regression (GWR) is a spatial data analysis method where spatially varying relationships are explored between explanatory variables and a response variable. One unresolved problem with spatially varying coefficient regression models is local collinearity in weighted explanatory variables. The consequence of local collinearity is: estimation of GWR coefficients is possible but their standard errors tend to be large. As a result, the population values of the coefficients cannot be estimated with great precision or accuracy. In this paper, we propose a recently developed method to remediate the collinearity effects in GWR models using the Locally Compensated Ridge Geographically Weighted Regression (LCR-GWR). Our focus in this study was on reviewing the estimation parameters of LCR-GWR model. And also discussed an appropriate statistic for testing significance of parameters in the model. The result showed that Parameter estimation of LCR-GWR model using weighted least square method is

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Statistical downscaling to predict drought events using high resolution satelite based geopotential data
Authors: Kuswanto H , Yuliatin I L , Khoiri H A
Published: June 2019

Drought prediction is a very challenging work due to high degree of uncertainty in the climate system. Geopotential height has been investigated as one of the dominant variables that can be used to predict drought events. This paper discussed the use of high resolution satelite based (reanalysis) data as the predictor of drought events, resulting on a high dimensional dataset. To deal with this, dimension reduction has been carried out by using Principle Component Analysis (PCA), prior to the development of the downscaling models which incorporate the past SPI (Standardized Precipitation Index) combined with the geopotential height at some specific atmosperic levels i.e. 500hPa, 850hPa, 900hPa, 975 hPa and 1000hPa. The SPI, as the drought risk measure is derived from the reduced dimension of precipitation data observed from the corresponding meteorological stations, while the geopotential height is reduced from gridded high resolution data. The downscaling process found the best model to predict the drought risk with various degree of R-squares. The outsample validation showed that predicting drought using SPI3 (three month period SPI) with geopotential at the 900hPa level as the predictor outperforms the others with R-square reaching 77%.
Optimal Control of an HIV Model with Changing Behavior through an Education Campaign, Screening and Treatment
Authors: Marsudi  , Trisilowati  , Suryanto Agus , Darti Isnani
Published: June 2019

Optimal control theory was used on the system of differential equations to achieve the goal of minimizing the infected population and slow down the epidemic outbreak. Necessary conditions of optimal control problem were rigorously analysed using Pontryagin’s maximum principle. Three control strategies were incorporated such as human education campaign, screening and treatment of infected human and its impact were graphically observed. Runge-Kutta forward-backward sweep numerical approximation method is used to solve the optimal control system. Numerical results with education campaign levels, screening and treatment rates as controls are illustrated.
Parameter Estimation and Statistical Test in Multivariate Adaptive Generalized Poisson Regression Splines
Authors: Hidayati Sri , Otok Bambang Widjanarko , Purhadi
Published: June 2019

Poisson regression is a standard model for data counts that can be used to determine these factors. Equidispersion is assumptions that must be met in poisson regression. Equidispersion is a condition that the average of response variable is equal with the variance of the response variable. In real cases, there are overdispersion or underdispersion cases. Generalized Poisson Regression (GPR) is one of method that can handle cases of overdispersion or underdispersion. Multivariate Adaptive Regression Splines (MARS) is a nonparametric regression that can handle data whose behavior changes in sub-intervals, so that there is a knot point that indicates the occurence of changes in data behavior patterns. Multivariate Adaptive Generalized Poisson Regression Splines (MAGPRS) model is used as the development of the MARS and Generalized Poisson Regression. This research use Weighted Least Squares (WLS) with Berndt Hall Hall Husman (BHHH) algorithm to obtain parameter model estimator. Afterwards, get the test statistic on the model Multivariate Adaptive Generalized Poisson Regression Splines using Maximum Likelihood Ratio Test (MLRT). Finally, the application of MAGPRS model was carried out in the case of the number of Acute Respiratory Tract Infection in babies.
Dynamical Analysis of Infected Predator-Prey Model with Saturated Incidence Rate
Authors: Pusparani Antika , Kusumawinahyu Wuryansari Muharini , Trisilowati
Published: June 2019

A predator-prey model with disease in both populations is proposed to illustrate the possibility of disease transmission between prey and predator through contact and predation. We used saturated incidence rate which takes behavioural changes of healthy population into consideration when disease spreads around them. The existence of eight non-negative equilibrium points is analysed and their local stability has been investigated. Numerical simulations are given to illustrate analytic results.
The Estimation Function Approach Smoothing Spline Regression Analysis for Longitudinal Data
Authors: Risnawati  , Rinaldo Fernandes Adji Achmad , Nurjannah
Published: June 2019

It is given the paired data following a nonparametric regression model for longitudinal data. The regression curve is approached by the smoothing spline function. The smoothing spline is a function that is able to map the data well and has a small error variance. This current study aims to obtained from completing PWLS (Penalized Weighted Least Square) optimaziton. Besides, the GCV method is used to select the smoothing parameter.
Random-Forest (RF) and Support Vector Machine (SVM) Implementation for Analysis of Gene Expression Data in Chronic Kidney Disease (CKD)
Authors: Rustam Zuherman , Sudarsono Ely , Sarwinda Devvi
Published: June 2019

The application of mathematics in the field of bioinformatics has been widely developed. For example Support Vector Machines (SVM) and Random Forest (RF) are state of the art for classification of cancer in many applications. One of them is Chronic Kidney Disease (CKD). CKD is one of the kidney diseases that sufferers are increasing and have symptoms that are difficult to detect at first. Later, microarrays in gene expression are important tools for this approach. Microarrays gene expression provides an overview of all transcription activities in biological samples. The purpose of this research is a hybrid model combining Random Forest (RF) and Support Vector Machine (SVM) can be used to classify gene expression data. RF can highly accurate, generelize better and are interpretable and SVM (called RF-SVM) to effectively predict gene expression data with very high dimensions. In addition, from the simulation results on data from the Gene Expression Omnibus (GEO) database, it is shown that the proposed RF-SVM is a more accurate algorithm on CKD data than RFE-SVM.
Modeling Inflation and Money Supply using Spatial Vector Autoregressive Model with Calendar Variation: Restricted vs Non-restricted Coefficient
Authors: Sumarminingsih Eni , Setiawan  , Suharsono Agus , Ruchjana Budi Nurani
Published: June 2019

One of the tasks of the government is to maintain price stability reflected in the stability of inflation through the regulation of the money supply. Therefore the government needs to know the forecast of the inflation rate and the money supply. In modeling inflation and the money supply simultaneously in Indonesia, three things need to be accommodated, namely the relationship between variables, the existence of space-time relationships and the effect of Eid al-Fitr. The spatial vector autoregressive model with calendars variation can accommodate these three things. The purpose of this study is to compare two types of spatial vector autoregressive models with calendar variations, namely restricted and non-restricted coefficient to model inflation and the money supply in Surabaya, Malang, Kediri, and Jember simultaneously. Results of this study indicate that the non-restricted spatial vector autoregressive model with calendar variation is better than the restricted one. This can be seen from the value of MSE of the non-restricted model that is smaller than the restricted model.
Spatio-Temporal Fay-Herriot Models in Small Area Estimation to Obtain Factors That Affecting Poverty in Polewali Mandar District
Authors: Suwarti  , Rumiati Agnes Tuti , Kuswanto Heri
Published: June 2019

Poverty is a classic problem in almost all regions in Indonesia both at the provincial and district levels. Polewali Mandar district is a district with the highest poverty rate in West Sulawesi Province. Handling the problem of poverty requires the availability of data to the smallest level so that the policies taken by the government can be right on target. One method for obtaining poverty estimates reaches the smallest area using the Small Area Estimation (SAE) method. Spatio-Temporal Fay-Herriot models is one of the SAE methods that has considered spatial and time effects. Auxiliary variables are needed in the SAE method to get good estimation results. Availability of auxiliary variables that affect poverty in Polewali Mandar district is very necessary. Therefore the purpose of this study was to obtain auxiliary variables that influence poverty in Polewali Mandar district. Bootstrap parametric procedures are used to obtain factors that influence poverty in Polewali Mandar district, while for spatial weighting matrices use customized contiguity based on the main business fields in the village. The response variable is the percentage of poverty in each village affected by the Susenas sample. The results obtained were the variables that affected poverty in Polewali Mandar district were the percentage of farm worker’s families, the percentage of the population receiving Jamkesmas / Jamkesda, ratio of population to number of micro and small industries, average number of household members, ratio of population to number of health facilities and percentage of families living on river banks.
Recursive Particle Swarm Optimization (RPSO) schemed Support Vector Machine (SVM) Implementation for Microarray Data Analysis on Chronic Kidney Disease (CKD)
Authors: Rustam Zuherman , Syarifah Mas Andam , Siswantining Titin
Published: June 2019

Chronic Kidney Disease is the second chronical and catastrophic disease after heart disease in terms of treatment cost. This is because CKD symptoms occurs on final stages, that is fourth and fifth, in which it is too late for treatment. Therefore, final stage patient must receive continuous medication, such as haemodialysis. So early detection on a patient CKD is necessary to prevent patient to be chronic. Studies of gene genes are used to classify microarray data with global CKD decisions or not. So to get accurate results in this study using SVM-RFE with the addition of the Particle Swarm Optimization algorithm as a gene selector to be more optimal and it consideration of the fixed gene in its condition which is important information of the CKD gene itself. This research is then expected to be able to classify globally with CKD output or not CKD. As a result, for the CKD microarray data accuracy using RPSO schemed SVM highest than only using SVM-RFE.
Modeling of HIV and AIDS in Indonesia Using Bivariate Negative Binomial Regression
Authors: Tohari Amin , Chamidah Nur , Fatmawati
Published: June 2019

The problem of HIV and AIDS in Indonesia is a frightening health problem with a number of cases that tend to increase each year. The aim of this research is to model the number of HIV and AIDS cases in Indonesia using bivariate negative binomial regression approach. Bivariate negative binomial regression is a regression method for modeling a pair of response variables in the form of count data with negative binomial distribution and correlating to each other. This research uses secondary data from the ministry of health in 2017 about the number of HIV and AIDS cases in Indonesia. From the results of this research, we obtained the deviance value of 38.9197 which was used to describe the goodness of fit test.
Stability Analysis and Optimal Control of Lung Cancer Growth Model with Education
Authors: Trisilowati
Published: June 2019

This study discusses the influence of smoking behavior of both active and passive smokers on the growth of lung cancer population through mathematical models. There are four population in this model, namely: susceptible population, active smoker population, passive smoker population, and population of lung cancer patients. The model is then analyzed using stability theory of nonlinear differential equations. Based on analysis result, the model has three equilibrium points: extinction equilibrium point, smoker-free equilibrium point and endemic equilibrium point. These equilibrium points are asymptotically stable under certain conditions. Moreover, education is involved as a control which is applied to susceptible population. The purpose of this optimal control is to minimize the population of smokers and lung cancer as well as the education costs. Pontryagin’s principle is then implemented to solve optimal control problems. Finally, numerical simulations are carried out to determine the effectiveness of the controls used.
Interval Parameter Estimation of Quantile Regression Using Bca-Bootstrap Approach with Application to Open Unemployment Rate Study
Authors: Ummah Solehatul , Ratnasari Vita , Prastyo Dedy Dwi
Published: June 2019

Parameter estimation in the linear regression model using ordinary least square (OLS) method is less precise to analyze data containing outliers. It is because outliers can cause unstable parameter estimate. In addition, the existence of outliers causes residuals to be larger so that the residual’s variance is not constant (heteroscedasticity). One model that is able to overcome the effect of outliers is quantile regression because it can accommodate the non-homogeneous variances in modeling. In this study, the confidence interval of the parameter estimate in the quantile regression model was obtained, i.e., the Bias-Corrected and accelerated (BCa) bootstrap method. The proposed method was applied in modeling the open unemployment rate in Indonesia in 2017. The quantile value used in this study is quantile 0.05, 0.5, and 0.95 with 1500 resampling in BCa-bootstrap approach. The empirical result shows that the best quantile regression model is obtained at the value of quantile 0.95 which has a Pseudo R2 value is 60.45 percent. The model at quantile 0.95 shows that the percentage of youth, economic growth rate, and labor force participation rate have a significant effect on the open unemployment rate in Indonesia.
A Maize Foliar Disease Mathematical Model with Standard Incidence Rate
Authors: Windarto  , Fatmawati  , Putri Kamara Mustiko
Published: June 2019

In this paper, we present a mathematical model of maize foliar disease with standard incidence rate. The present model is an improvement model from Collins and Duffy, where Collins and Duffy consider a mathematical model with the bilinear incidence rate. The present model has two equilibria namely the disease-free equilibrium and endemic equilibrium. We find that the disease-free equilibrium is asymptotically stable whenever the basic reproductive ratio is less than one. On the other hand, the endemic equilibrium will exist and be asymptotically stable whenever the basic reproductive ratio is greater than one. Furthermore, we perform numerical simulations to confirm the analytical results.
Soft Tissue Tumor Classification using Stochastic Support Vector Machine
Authors: Zahras Durrabida , Rustam Zuherman , Sarwinda Devvi
Published: June 2019

As healthcare is becoming one of the most rapidly changing industries by the increasing type of diseases, technology plays an important role in helping medical staffs solve those medical problems. Soft tissue tumors are tumors in the musculoskeletal system that involve soft tissue (tissue other than bone tissue). It includes muscle tissue, nerves, blood vessels, fat, and connective tissue. This soft tissue tumor is divided into two, namely benign and malignant. To prevent any medical errors in classifying patients’ data, one machine learning called Stochastic Support Vector Machine is being studied. In this study, we will evaluate soft tissue tumor patients’ data in Nur Hidayah Hospital, Yogyakarta, Indonesia using Stochastic Support Vector Machine to see its accuracy. The result is encouraging that Stochastic Support Vector Machine works better than the original Support Vector Machine.
Potential Fatty Acid Composition of Hermetia illucens Oil Reared on Different Substrates
Authors: Alifian M D , Sholikin M M , Evvyernie Dwierra , Nahrowi
Published: June 2019

Hermetia illucens larvae (HiL) has been studied because of its capability to break down organic waste. HiL can convert waste biomass efficiently, that can be used as future feedstuffs. This study aimed to evaluate the fatty acids composition from HiL oil (HiLO) which reared on the different substrates. The experimental was compared of (1) HiL reared on palm kernel meal and (2) HiL reared on 80% industrial waste mix with 20% organic waste. The chemical composition of HiL measured base on the Association of Official Analytical Chemists (AOAC). The Hermetia illucens larvae oil (HiLO) was extracted according to the modification of the Soxhlet extraction procedure. Fatty acid compositions were analyzed using gas chromatography (GC). The data collected and analyzed as descriptive. The results of this study ether extract content of HiL (1) 51.46% higher than HiL (2), this is due to substrate types. Fatty acids of both are almost the same and the most dominant are lauric acid 40.54% and 46.72%, oleic acid 17.48% and 15.98%, palmitic acid 14.55% and 12.12% and myristic acid 15.57 and 11.13 %, respectively for each HiLO (1) and (2). The conclusion of this study is the HiL reared on different substrates affect lipid content but the fatty acid composition is similar.
Bioactivity of Flavonoid in Ethanol Extract of Annona squamosa L. Fruit as Xanthine Oxidase Inhibitor
Authors: Alvionita Mieke , Oktavia Ira , Subandi  , Muntholib
Published: June 2019

The global gout prevalence was increased rapidly in recent decades, especially in some developing countries. One of the most commonly used to treat gout is allopurinol, that act as xanthine oxidase inhibitor. However, consuming allopurinol in the long term can cause some unwanted side effects. On the other hand, many kinds of flavonoid compounds identified in some Indonesian grown plants have bioactivity as xanthine oxidase inhibitor. One of that is sugar apple (Annona squamosa L. fruit). Therefore, the aims of this study were to isolate the flavonoid compounds in ethanol extracts of sugar apple and to test the activity as xanthine oxidase inhibitor relative to allopurinol. The study has been carried out in some phases: (1) flavonoid extraction using 70% ethanol, (2) purification of the flavonoid isolate using n-hexane, chloroform and ethyl acetate as solvent, (3) flavonoids identification and (4) inhibitory activity test against xanthine oxidase, relative to allopurinol using spectroscopy methods. The results have shown that: from 275 grams of sugar apple fruit can be isolated 6 grams of flavonoid with the purity of 95.26% (according to HPLC peak) and has xanthine oxidase inhibitory activity was higher (83%) than allopurinol (48%) at the same concentration (100 ppm). Moreover, based on in silico study, there was also confirmed that a flavonoid compound found in Annona squamosa L., has higher binding affinity to the xanthine oxidase than allopurinol. This result thus indicated the flavonoid isolated from Annona squamosa L. might be a promising herbal drug for gout treatment.
Effect of Mixed Inoculums Volume and pH on Anti Nutritional Level in Cabbage Fermentation using Saccharomyces cerevisiae and Lactobacillus plantarum
Authors: Ananda Tinok Dwi , Srihardyastutie Arie , Prasetyawan Sasangka , Safitri Anna
Published: June 2019

Cabbage (Brassica oleracea var. capitata) that is one of the widely consumed vegetables, contains significant amounts of anti-nutritional components, such as tannin. This component can be reduced by fermentation, where bacterial tannase activity is able to degrade tannin into glucose and gallic acid. A simultaneously mixed cultures fermentation using Saccharomyces cerevisiae and Lactobacillus plantarum has been developed because they possess some mutualism interaction that can be beneficial in the fermentation process. Therefore, this research was focused on the effect of mixed inoculums volume of S. cerevisiae and L. plantarum and initial culture pH on the tannin and glucose level during cabbage fermentation. The sliced cabbage was inoculated with simultaneously mixed cultures (volume ratio of yeast and bacteria used was 1:1) at a different volume range 5%-25% (v/v) and also various pH range from 4 to 7, and then incubated at room temperature in anaerobic condition for 4 days. Tannin and glucose level in fermented cabbage (both biomass and filtrate) were determined using Folin-Denis and phenol-sulphuric method, respectively. The using of 5% mixed inoculums volume and initial pH around 7 were found to be the optimum condition for tannin degradation in cabbage. The remained tannin level in these fermented cabbage decreased up to 18.58% (54.061 mg/100 g FW). This experiment reveals that the amounts of inoculums and initial culture pH affected tannin degradation during cabbage fermentation using mixed cultures of yeast and lactic acid bacteria.
Effect of DMSO concentration on the quality of goat fetus fibroblast cell cultured in vitro
Authors: Karima H N , Susilawati Trinil , Djati M S , Ciptadi Gatot , Setiyawati  , Putri Ardyah R I
Published: June 2019

Dimethyl sulfoxide (DMSO) is one of the cryoprotectants that have been used in cell freezing. Cryoprotective agents are necessary to deal with damage in cells associated with slow freezing. Goat foetuses are obtained from local slaughterhouse in Sukun, Malang, East Java. Using various DMSO concentration that were 0% control, 5%, 10%, and 15%. The cell was free with slow freeze methods using Mr. Frosty in -20°C. After 24 days, the samples were analyzed for their viability, size, and abnormality. The result shows the cell size ranged from 3 µm until 5 µm in all samples, categorized as small cell. In viability is significantly influential on 10% DMSO concentration of 92%, while at 0% concentration is 0%, 5% concentration is 56%, and 15% concentration is 89.67%. The abnormality in DMSO 0% all cells are dead and the tissue isn’t developing, in DMSO 5% the abnormality is 3.17%, DMSO 10% is 2.5%, and DMSO 15% 5.67. From the results, we can conclude that the concentration of 10% of DMSO is the best concentration to be used as a freezing method for goat fetus cells.
Alkaloid Fraction of Litsea glutinosa Leaves Provides an Important Precursor for Inhibition of Dipeptidyl Peptidase 4 Activity
Authors: Kisnawaty S W , Nityasewaka P , Sukma B A R , Putrinadia A V , Ma’rifah T , Tamtomo D G , Indarto D
Published: June 2019

Dipeptidyl Peptidase-4 (DPP-4) is a serine protease that plays an important role in metabolic and immunological functions. DPP-4 inhibitor is an alternative oral drug for the therapy of patients with Type 2 Diabetes Mellitus who do not respond to the standard therapy (metformin). However, long term uses of this drug remain unknown. Therefore, this study aimed to identify a phytochemical that could inhibit the DPP-4 and to extract it. This biocomputational study used a molecular docking method. Three-dimensional structure of DPP-4 and sitagliptin was downloaded from Protein Data Bank with access code PDB 3F8S and ZINC database with access code ZINC22007143. Indonesian phytochemicals were selected as research samples, which had 3 D structure and met the criteria of Lipinski. Leaves of L. glutinosa were extracted using the soxhletation method with ethanol solvent of which alkaloid fraction was generated with phosphoric acid, n-hexane and chloroform solvents. Boldine concentration in extract and alkaloid fraction of L. glutinosa leaves was quantified using the High Performance Liquid Chromatography device. Actinodaphnine interacted with the catalytic triad of DPP4 (Ser 630 and His 740) and had three additional residues to bind to DPP-4 as same as sitagliptin (Glu 205, Glu 206 and Tyr 662). Naturally, actinodaphnine was synthesized from boldine. Total boldine concentration in L. glutinosaextract and alkaloid fraction were 1.11 and 2.14 mM respectively. Boldine as the precursor of actinodaphnine was successfully isolated from L. glutinosa leaves and will become a promising phytochemical for drug development of DPP-4 inhibitor.
Potential of lactic acid bacteria from asam durian as a probiotic candidate for chicken
Authors: Putri Audina , Wiryawan Komang Gede , Toharmat Toto , Suharti Sri
Published: June 2019

The use of antibiotics as a growth promoter for chickens may develop resistance to pathogenic bacteria in the digestive tract of chickens. Other negative impacts on food safety came from antibiotic residues. One alternative that can be used as a substitute for antibiotics is probiotics. Probiotics derived from lactic acid bacteria (LAB) is safe beside that it is potential to improve growth and chicken health. This study aimed to obtain LAB isolates from asam durian which is a local food in West Sumatera. This study consisted of several steps i.e., isolation, identification, antagonistic test to patogenic bacteria and isolates survival in the gastrointestinal tracts. Results of this study found that 8 isolates of LAB were morphologically identified with negative catalase and gram-positive bacteria. All LAB isolates had inhibitory activity to Escherichia coli. The diameter of the inhibitory zone was used to select the potential of LAB and further tested for their survival in the digestive tract at pH 2, 4 and 6 and 0.5% bile salts. Isolate P1 and isolate P3 had inhibitory zone diameters of 17.35 mm and 16.08 mm, respectively, which could survive at the pH of 2, 4 and 6 and 0.5% bile salts. It is concluded that isolate P1 and isolate P3 from asam durian have the potential as probiotics for chickens because they inhibit the growth of pathogenic bacteria and can survive in the gastrointestinal conditions.
The Rice Bran as Therapy Agent to Decrease the SGOT/SGPT activities and Improve the Histopathology of Liver in White Rat (Rattus norvegicus) Induced by High Cholesterol Diet
Authors: Roosdiana Anna , Hendrawan Viski Fitri , Wulandari Mimin
Published: June 2019

Hypercholesterolemia is a metabolic disorder on increase of total cholesterol levels in blood exceeding normal values. The high cholesterol levels in the blood will be balance by converting to bile acids. The synthesis of bile acids will produce the excessive free radicals leading to oxidative stress. The oxidative stress cause lipid peroxidation of hepatic cell membranes that will increase SGOT and SGPT activities in the blood and changes in the histology of the liver. The content of crude fiber and antioxidants in rice bran are able to overcome the hypercholesterolemia. This study aimed to determine the effect of rice bran as a therapy in white rats (Rattusnorvegicus) high-cholesterol diet model on SGOT and SGPT activities and histopathologic images of liver. Rats were divided into 5 groups, namely: negative control group, positive control group, rice bran therapy group with dose 16%/rat/day, 38%/rat/day and 57%/rat/day. Rice bran therapy performed for 21 days. SGOT and SGPT activities were determined by spectrophotometry and hepatic histopathologic images were observed with HE (Hematoxylin-Eosin) staining. The levels of SGOT and SGPT were analyzed by one-wayANOVA with α = 5% and histopathology of liver was analyzed descriptively. The results showed that rice bran with dose of 57%/rat/day significantly (p <0.05) can decrease SGOT and SGPT activities. Histopathologic observations showed that antioxidants in rice bran could reduce fatty acids on hepatic histopathology. The dosage of 57%/rat/day showed to decrease SGOT, SGPT activities and can reduce fatty acids on hepatic. It can be concluded that the administration of rice bran can reduce the activities of SGOT, SGPT and improve the histopathology of liver rat induced by high cholesterol diet.
Antibacterial and radical scavenger activities of extract and compounds of Wualae (Etlingera elatior) stems from Southeast Sulawesi
Authors: Sahidin I , Wahyuni  , Malaka M H , Fristiohady Adryan , Saleh Ahmad , Marianti A
Published: June 2019

Two known compounds, namely stigmast-4-en-6β-ol-3-one (1) and p-hydroxybenzoic acid (2) are firstly reported from stems of E. elatior. Isolation were carried out by chromatography technique including Thin Layer Chromatrography (TLC), vacuum liquid chromatography (VLC) and radial chromatography (RC) with silica gel as adsorbent and mixture of solvents as eluen. Structure of isolated compounds were determined by spectroscopy methods i.e. FTIR, 1H and 13C NMR and also by comparison the spectroscopies data with the same data from references. Biological activities of isolated compounds evaluated against some bacteria consist of Bacillus subtilis FNCC 0060, Escherichia coli ATCC 35218, Pseudomonas aeruginosa ATCC 27853, Salmonella enterica ATCC 14028, Staphylococcus aureus ATCC 25923, dan Streptococcus mutans ATCC 25175 and also against DPPH (2,2-diphenil 1-pichylhydazyl) radical as antiradical scavenger activity. The result showed that generally, antibacterial potency those samples i.e. methanol extract, stigmast-4-en-6β-ol-3-one and p-hydroxybenzoic acid less active than positive control (chloramphenicol). Individually, antibacterial activity of p-hydroxybenzoic acid > methanol extract > stigmast-4-en-6 β-ol-3-one. In addition, p-hydroxybenzoic acid is the most active against S. mutans. Radical scavenger activity of tested samples is less active than than positive control (ascorbic acid). Furthermore, the radical scavenger potency of p-hydroxybenzoic acid > methanol extract > stigmast-4-en-6 β-ol-3-one.
The inhibitory effect of Andrographis paniculata extract on proliferation of breast cancer cell line
Authors: Sholihah M M , Indarto D , Pramana T Y
Published: June 2019

Aerobic glycolysis is commonly used as the main energy source for cancer cell growth. Adenylate kinase 2 (AK2) plays an important role in maintenance of ATP production in the mitochondria.NeoandrographolideinAndrographis paniculatapotentially inhibit AK2 activityin silico. This study aimed to investigate the inhibitory effect ofA. paniculataextract on proliferation of breast cancer cell line. This experimental laboratory used MCF-7 cell line andA. paniculataplants, which were extracted using the maceration method with 70% ethanol.Neoandrographolideconcentration inA. paniculataextract was determined using HPLC. A total 1x104MCF-7 cells were incubated for 24 hours with or without 0.4% (v/v) dimethyl sulfoxide as solvent (SC) or negative control (NC) group. The same amount of MCF-7 cells was treated withA. paniculataextract with 3 different dosages: 222 ppm (AE1), 111 ppm (AE2) and 55.5 ppm (AE3). The inhibition of cell proliferation used the 3-(4,5-dimetiltiazol-2-il)-2,5-difeniltetrazolium bromide (MTT) assay. Data were analyzed using ANOVA and LSD tests with p value <0.05.Ethanol extract ofA. paniculatacontained 4.43 µMneoandrographolide.The inhibition of MCF-7 cell proliferation was found in AE1 (47.98%) and AE2 (30.50%) groups and was significantly different from the NC group. While the percentage of MCF-7 cell inhibition in the AE1 group differed from NC (p = 0.002) and SC (p = 0.013) groups. Ethanol extract ofA. paniculatacan inhibit MCF-7 cell proliferation. Further Study is needed to investigate the role ofneoandrographolideon inhibition of AK2 activity in MCF-7 cells.
The activity of Flavonoid Isolates from Papaya (Carica papaya L.) Seed as Pancreatic Lipase Inhibitor
Authors: Subandi  , Utami Pancasari Wiji , Brotosudarmo Tatas H.P.
Published: June 2019

Excessive fat consumption can cause obesity, which is currently one of the global problems, because it can trigger various diseases such as coronary heart disease, diabetes, and so on. Absorption of fat into the body requires pancreatic lipase enzymes, which can be reduced by lipase inhibitors such as orlistat drugs. Previous research has shown that the extract of papaya seed, which contains many flavonoids, was able to inhibit pancreatic lipase. Therefore, the aims of this study are to isolate and identify the flavonoid compounds from papaya seeds that are active as pancreatic lipase inhibitors. Papaya seed powder was extracted using ethanol 70%, followed by isolation using TLC, identification by phytochemical test and UV and IR spectroscopy, while pancreatic lipase inhibitory activity has been done using titrimetric method. To confirm the Inhibitory activity of the predicted flavonoid against the enzyme, also had been done in silico study. The results had shown that there are two types of flavonoid in the ethanol extract of papaya seed, that are active as pancreatic lipase inhibitors. The two flavonoid isolates have inhibition power of 132 and 12 times stronger than orlistat in the same mass. Result of UV-VIS and IR spectrum has shown that both isolates were suspected to have a similar structure to the three flavonoid compounds: epicatechin, catechin or epigallocatechin-3-gallate (EGCG). In silico study, also confirmed that each of the predicted flavonoids has higher binding affinity against pancreatic lipase, than orlistat.
Sugar-Rich Hydrolyzates from Coffee Pulp Waste which Produced under Solid State Fermentation by Pestalotiosis sp. VM9 and Aspergillus sp. VTM5, and Its Efficiency as Medium for Single Cell Protein Saccharomyces cerevisiae
Authors: Ubaidillah Syafiq , Muzakhar Kahar
Published: June 2019

Polysaccharides rich coffee pulp is one of some abundant agricultural waste in Indonesia. The pulp also contains protein which may lead to be an important source for industrial bioprocessing. Under solid-state fermentation (SSF) by Pestalotiosis sp VM9 using of this pulp, reducing sugar was produced 392.35 μg/ml after 6 days incubation at 30°C. Meanwhile, SSF of the pulp by Aspergillus sp. VTM5, after 5 days of incubation 446.6 µg/ml of reducing was released. The investigation proved that the hydrolyzates medium which were produced under SSF by Pestalotiosis sp VM9 and Aspergillus sp. VTM5 can be used as a source for single cell protein (SCP) Saccharomyces cerevisiae production. The SCP productions using both hydrolyzates were1.89x106 2.9x106 cell/mL after 54 and 48 hours of incubation at 30°C. Furthermore, during SCP production, S. Cerevisiae consumed sugars as carbon sources in a range of 189.8-225.5 μg/ml (49.5-51.6%) from initial concentration. From the results, it is suggested that the coffee pulp waste can be used as a cheap medium for SCP production. Further investigation to improve SCP production efficiency, optimizing of hydrolysis under SSF and analysis of hydrolyzates component were needed.
Identification of MicroRNAs Targeting mTOR Gene Transcripts in Skin, Lung, Kidney, Uterus and Breast Cancer
Authors: Hadi Wibowo Stefanus Satrio , Agustriawan David , Parikesit Arli Aditya , Nurdiansyah Rizky
Published: June 2019

mTOR constitutively activated during tumorigenesis to stimulates mRNA translation through regulating cell energy metabolism. Using in silico approach based on miTS method, correlation analysis, and meta-analysis method, miRNA biomarker related to five cancer were researched. The input of the pipeline was THCA patients from GDC Data Porta ID and was processed using TCGA2STAT, dplyr, and metacor package in R studio, Excel, and MirTarBase. This study aims to discover the significance level of mTOR in five cancer: HNSC (Head and Neck Squamous Cell), lung adenocarcinoma (LUAD), Kidney Renal Clear Cell Carcinoma (KIRC), Uterine Corpus Endometrial Carcinoma (UCEC), and Breast Invasive Carcinoma (BRCA). Our study shows that in the cancer patient, mTOR tends to support cancer growth despite miRNA targeting it has low correlation rho value. The numerous microRNAs targeting mTOR have a specific role in each tissue, meaning it can be targeted as a precise medicine.
Catalytic synthesis of diethyl carbonate via one-pot reaction from carbon dioxide, ethanol, and epoxide
Authors: Anggerta L A , Kurniawansyah Firman , Wibawa Gede
Published: June 2019

Carbon dioxide is one of the responsible substances of the global warming effect. Gasoline consumption had increased significantly each year, it leads to the intense elevation of particulate matter and carbon dioxide compound in the atmosphere, which are the products of combustion of fuel. Carbon dioxide is possibly converted to high valued compound, diethyl carbonate (DEC) is one of the alternative compounds that is being employed as an additive for fuel to diminish the emission with increasing octane number of the fuel. The objective of this study was to research and develop a technology of direct synthesis of DEC from Carbon dioxide, ethanol, epoxide as dehydrating agent and KI/Sodium Ethoxide and KI/Zeolite catalysts. Operation condition in this experiment had an initial pressure of 35 bar and temperature of 170°C. Further, the effects of KI/Sodium Ethoxide and KI/Zeolite catalysts were examined to the performance of DEC synthesis. In addition, the influence of the type of dehydrating agent (epoxide), which was propylene oxide and butylene oxide was investigated as well. Subsequently, the products were analyzed using gas chromatography-mass spectrometry for qualitative analysis and gas chromatography for quantitative analysis. The results showed that DEC was successfully synthesis from carbon dioxide, and the optimum yield was obtained from the use of KI/Zeolite catalyst, propylene oxide as a dehydrating agent.
Integrated of Sequences Seismic Stratigraphy, Accoustic Impedance Invertion, and Petrophysical for Resources Exploration in Offshore Southern Ardjuna Northwest Java Basin, Indonesia
Authors: Indah M S , Haris Abdul , Natsir M
Published: June 2019

This thesis discusses the uses of the integration of the Stratigraphic Seismic Sequence method, AI Inversion, Petrophysical Evaluation for Exploration Resource Analysis in more detail and more accurately which will produce information on contingent structures ranging from Play concepts, petroleum systems, and properties from reservoir characteristics, to prospect mapping. and evaluation of the risk of exploration findings. Understanding of seismic internal characteristics helps draw stratigraphic sequential seismic markers in seismic cross sections. The Seismic AI invasion will help in the determination of the spread of lithofasies, porosity, fluid in seismic sections. Distribution Map of AI Inversion of Structure Overlays The depth of the interval TST 2 provides trap area parameters for Sand DST 4 located on the Tidal System. Petrophysics will help provide porosity properties, netpay thickness, formation water saturation. The use of this integration method will prove if the evaluation of subsurface data is assessed by Integration of Seismic and Geophysical Methods (Seismic Inversion, Seismic Attribute Analysis, Seismic Stratigraphy Analysis) and Wells Data (DST test data, Fossil Index Catalog, and mud log well) very helpful for evaluating the Half Graben Exploration Resources in an integrated manner.
Application of Particle Swarm Optimization BP Algorithm in Air Humidity of Greenhouse Crops
Authors: Li-Li Guo , Yong Liu , Zi-Wei Liu , Hua-Wei Sun
Published: June 2019

The advancement of artificial intelligence, the synonym of precision agriculture has approached the public’s vision, and the different requirements for air humidity in different growth periods of crops are proposed. The BP neural network optimized by particle swarm optimization algorithm is proposed to predict the air humidity of crops. Algorithm, this paper chooses BP algorithm network topology structure is 2-5-1, improves the inertia weight of PSO algorithm, proposes nonlinear inertia weight reduction strategy

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, trains BP algorithm with improved PSO algorithm, has no gradient information, jumps out local pole Value, reduce the number of iterations of the algorithm, and speed up the training speed of the neural network. According to the experimental results of MATLAB simulation, the air humidity prediction model of particle swarm optimization neural network is constructed, which proves the effectiveness of the improved particle swarm neural network prediction system. It can be shown that the proposed algorithm has a relative error of at least 0.0134 compared with other algorithms.