bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analyzing Netizens’ Perceptions Towards Indonesian Presidential Candidates Using Topic Modeling Approach
Authors: Karolita Devi , Lestari Ariesta 
Published: June 2019

Abstract
Over the past few years, Twitter has significantly grown as the microblogging platform. Millions of user use this platform to share their attitudes, views, and opinion on a daily basis. This phenomenon has been used to promote people’s attention towards some event, such as 2019 Indonesian Presidential Election. In this study, we investigate people’s online opinions towards the event through social media. The goal of the study is to discover frequent topics amongst netizens’ tweets during the election campaign. We collected tweets containing the names of the candidates, then applied topic modelling approach using Latent Dirichlet Allocation (LDA) method to cluster the topics. Based on the experiment, the tweets are clustered into ten topics with different focuses e.g., a topic discusses the candidate’s position towards sensitive issues, a topic about the community supports towards one presidential candidate. Our result shows that topic modelling approach can be used to analyse people’s perception in social media towards an important event.
Ovarian Cancer Classification using Bayesian Logistic Regression
Authors: Octaviani Theresia Lidya , Rustam Zuherman , Siswantining Titin 
Published: June 2019

Abstract
Cancer is one of the most common cause of death. One of the diseases that can be threaten women all over the world is ovarian cancer. Ovarian cancer is the eighth type of cancer that most women suffer from. Estimated that around 225.000 new cases are detected every year and around 140.000 people die each year from ovarian cancer. Based on WHO data, published in 2014, in Indonesia 7,6% of all cancer deaths are caused by ovarian cancer. So far there is no effective screening method for ovarian cancer. Current screening applications for high-risk women are still very controversial. There are many classification techniques has been applied for ovarian cancer prediction, for example deep learning, neuro fuzzy, neural network, and so many more. In this paper, we propose Bayesian logistic regression for ovarian cancer classification. We use data of patients suffer from ovarian cancer from RS Al-Islam Bandung to demonstrate the method. The accuracy expectation in this paper around 70%.
PSO-KS Algorithm for Fitting Lognormal Distribution: Simulation and Empirical Implementation to Women’s Age at First Marriage Data
Authors: Sarwo Prasojo Ari Purwanto , Prasetyoputra Puguh 
Published: June 2019

Abstract
Lognormal distribution plays an essential role in the distribution modeling of right-skewed data in many areas. In social sciences, for instance, it can be used to model women’s age at first marriage pattern, a key indicator in studying fertility patterns. Distribution fitting is a fundamental and essential stage of data modeling before doing advancing the analysis. Kolmogorov-Smirnov (KS) distance is applicable as maximum goodness-of-fit (GOF) estimators for distribution parameters. Minimizing KS distance is optimization problem. Particle swarm optimization (PSO) algorithm is a general optimizer that can handle various optimization problems. This study assesses the characteristics of minimum KS distance estimator for lognormal distribution parameters. KS distance estimators were obtained via optimization using the PSO algorithm, so the combination of these is called the PSO-KS algorithm. We conducted a simulation to assess the performance of PSO-KS, Maximum Likelihood (MLE), Method of Moment (MME). The bias and mean square error (MSE) of point estimators were used in simulation to assess the characteristics of estimators. Meanwhile, MSE of distribution fitting, KS distance, and log-likelihood value were used to evaluate the GOF characteristics. Moreover, we demonstrated the performance of the algorithm by implementing it to women’s age at first marriage data in Indonesia. The results show that based on the bias and MSE properties, the PSO-KS point estimators yield similar characteristics with MLE, but better than MME. From the GOF perspective, PSO-KS outperforms in MSE of distribution fitting and KS distance, but not in log-likelihood value. We also observed these patterns in the women’s age at first marriage data. The contributions of this study are two-fold, first to assess the PSO-KS algorithm in the lognormal distribution case. Second, it implements the algorithm on women’s age at first marriage data, which has broad social, economic, and public health implications.
Small Area Estimation with Bivariate Hierarchical Bayes (HB) Approach to Estimate Monthly Average per Capita Expenditure of Food and Non-Food Commodities in Province of Bali
Authors: Purwa Taly , Rumiati Agnes Tuti , Zain Ismaini 
Published: June 2019

Abstract
Small Area Estimation (SAE) is an indirect method that has been widely used for estimating parameters in a small area or small domain by borrowing strength of predictor variables from census or registration. This study uses Hierarchical Bayes (HB) method under the univariate and bivariate Fay-Herriot (FH) model to estimate monthly average per capita expenditure of food and non-food commodities for each district level in Province of Bali in 2014. Then estimation results from both models will be compared. The bivariate FH model is expected to increase the accuracy of the results of estimation by taking into account correlation between two types of expenditure rather than perform univariate estimation separately. Thirteen predictor variables from the administrative record of village data (PODES 2014) are included in each model as factors that affect these two types of expenditure. From the result, there are three variables that have significant effect on food expenditure, both in univariate and bivariate FH model. While, for non-food expenditure both model show different result on significant variables. Based on the results of the performance comparison, the best model is bivariate FH model since it has smaller Mean Square Prediction Error (MSPE), Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) value than univariate FH models. In addition, the bivariate FH model produces shorter 95% credible interval of estimated values. These conditions indicate that jointly modeling can improve the accuracy of estimation. Bivariate FH also produces significant improvement in adjusted R
2 value. Finally, the mapping result shows the same pattern for two types of expenditure. The highest monthly average per capita expenditure is more localized in the southern districts of Bali. While the lowest expenditure is more localized in the eastern and western districts of Bali.
Standard Growth Chart of Weight for Height to Determine Wasting Nutritional Status in East Java Based on Semiparametric Least Square Spline Estimator
Authors: Ramadan W , Chamidah N , Zaman B , Muniroh L , Lestari B 
Published: June 2019

Abstract
Wasting is a condition of a children characterized by a lack of weight by measuring weight for height. Currently, to monitor the growth conditions for childrens in Indonesia, we use the Towards Healthy Card called as Kartu Menuju
Sehat (KMS) which is guided by WHO 2005. The samples used to design WHO-2005 standard charts are children from Brazil, Ghana, India, USA, Norway, and Oman that have different physical conditions from children in Indonesia. Therefore, the using of standards growth charts from other countries cause incompatibility with Indonesian’s children growth. To illustrate the growth patterns of children in East Java, we use the semiparametric least square spline estimator that gives more flexible pattern. In this study we used weight (kg) as a response variable, height (cm) as a predictor variable for nonparametric component, and gender as a predictor variable for parametric component. The results show the semiparametric least square spline estimator can explain the growth patterns of children well because it has determination coefficient (R2) of 99.78% and mean square error (MSE) of 0.0353. The standard chart of weight for height of boy is higher than that of girl and percentage of wasting nutritional status of girl greater than that of boy.
A Dynamics Behaviour of Two Predators and One Prey Interaction with Competition Between Predators
Authors: Savitri Dian , Suryanto Agus , Kusumawinahyu Wuryansari M , Abadi  
Published: June 2019

Abstract
This research focuses on the dynamical of a Leslie-Gower predator-prey model with competition on predator populations. The model represents an interaction between one prey and two predator populations. The analysis shows that there are four equilibrium points, namely the extinction of predator populations point, the extinction of the first predator population point, the extinction of the second predator and the interior point. The existence of the interior equilibrium point is investigated by using Cardan criteria. Local stability analysis shows that both predator populations have never been extinct together. The second and third equilibrium point is local asymptotically stable under some conditions. Numerical simulations are carried out to investigate the stability of the interior point as well as to show that more than one equilibrium point may be asymptotically stable together for a set of parameter.
Simulations Study Combined Estimator Fourier Series and Spline Truncated in Multivariable Nonparametric Regression
Authors: Wayan Sudiarsa I 
Published: June 2019

AbstractThe problems one of that appeared in everyday life is how to explain the shape of the relation pattern between a response with some predictor. Regression analysis is a statistical method used to estimate the relation pattern between response (y) with predictor (x). Development of nonparametric regression of Fourier series involving multiple predictor, has been more developed for predictors of the same pattern. We need to develop different estimator for different predictors of multivariable nonparametric regression. Theoretical research will be focused on estimator form, and applied to simulation data. The estimation of the combined regression function of the Fourier and spline truncated sequence is obtained through the optimization of penalized least square (PLS). Based on the simulation result obtained that the larger the sample size and the smaller the size of the variance, it will result in better estimation value of parameter and knot.
Food Security of Farmer Households in The Papua Border Region In The Era of Industrial Revolution 4.0: Ordinal Logit Regression Model
Authors: Widati Agatha W. , Darwanto Dwidjono H. , Masyhuri  , Waluyati Lestari R. 
Published: June 2019

Abstract
This study aims to determine the factors that influence the food security of farmer households in the Papua border region. Twelve factors used in this study are maternal education, number of family members, price of rice, price of sweet potatoes, prices of cooking oil, prices of instant noodles, income, area of arable land, distance of buying food, share of food expenditure, reception of the rice for poor families (raskin), and farmer status (either local or transmigrant). This research uses primary data from direct interviews by asking a list of questions to farmer households in Jayapura City and Keerom District. The samples are randomly selected, and the total respondents are 160 farmer households, then the data analyzed by Ordinal Logit Regression. The results show that most of the household farmers classified as the food secure condition. Partially the number of family members, cultivated land area, the share of food expenditure and the price of sweet potato/cassava have a significant effect the probability of the occurrence of food security for farmer households significant at the 5% level of error, while dummy raskin significant at an error rate of 10%. The cultivated land area and dummy raskin have a positive effect on the food security of farmer households, while the number of family members, the price of sweet potato/cassava, and the share of food expenditure have a negative effect on farm household food security.
Identification of Epigenetic Regulation on The Expression of The Aberrant Gene of Kidney Renal Clear Cell Carcinoma Patients Observed in a Specific Race
Authors: Agustriawan David , Mulyono Hardi , Parikesit Arli Aditya , Nurdiansyah Rizky 
Published: June 2019

Abstract
Aberrant expression of genes in cancer is mainly caused by a mutation where there is a change in DNA sequences. However, the aberrant expression was also found without a change in the DNA sequences where epigenetic modification such as DNA methylation, histone modifications and microRNA become the main regulator in another layer of the cancer mechanism. The nature of epigenetic is heritable and reversible. It is important to search for the epigenetic mechanism in disease development in order to design epigenetic therapy and drugs. Methylation inhibitors and HDAC inhibitors drug already yielded seven FDA approved epigenetic drugs for myelodysplastic syndrome, cutaneous T-cell lymphoma, Multiple myelomas, peripheral T-cell lymphoma. This study search for the epigenetic mechanism in a kidney renal cell carcinoma patients in a white race. The dataset of transcriptome profiling and epigenetic was downloaded from The Cancer Genome Atlas (TCGA) database. Some programming languages such as R, Python, Matlab and MySQL database were used to pre-processing the datasets and correlation computation part. This study found 14 aberrant genes which significantly correlated with 19 aberrant methylation probes with the correlation score less than equal to -0.7 and p-value < 0.01. Some of those down-regulated genes such as ZNF542, ZFP28, TMEM25, STK33 are correlated with hypermethylation in more than one sites. It is suggested that those methylation sites can affect the down-regulation of their expression in cancer formation. Further study is needed to validate the results through wet lab analysis.
Submerged-Fermentation of Brassica oleracea L. capitata using Lactobacillus plantarum to Reduce Anti-Nutrient Compound
Authors: Fahmia Aulin Risyda , Srihardyastutie Arie , Prasetyawan Sasangka , Safitri Anna 
Published: June 2019

Abstract
Fermentation of cabbage (Brassica oleracea L. capitata) by Lactobacillus plantarumhas been successfully conducted using submerged-fermentation technique. The aims of this study is to determine the correlation between tannins and total sugar in the fermentation of cabbage. Fermentation process is proposed to reduce the concentration of tannins as anti-nutrient compound in cabbage. The tannin concentrations are determined using spectrophotometric method. Tannase enzyme produced by L. plantarum is hypothesised to be mainly responsible for the degradation of glucoside bonds, thus, reducing tannins contents. Total sugar contents were also investigated in this fermentation process. Fermentation process was carried out with variation of L. plantarum inoculum concentrations of 5%, 10%, 15%, and 20% (w/v). Results showed that the tannins value in cabbage raw materials was 290.877 mg/g FW. After fermentation process the optimal inoculum concentration reduced tannins concentration to 75.938 mg/g FW, at 5% inoculum concentration and pH 6for 96 h at 25 ºC. The correlation between tannins and total sugar in cabbage fermentation was found inversely proportional.
Actinodaphnine and Rutacridone as New T-Cell Protein Tyrosine Phosphatase Inhibitors for Drug Development of Obesity
Authors: Fitrianingrum Y , Indarto D , Kusumawati R , Suselo Y H 
Published: June 2019

Abstract
T-Cell Protein Tyrosine Phosphatase (TCPTP) is an obesogenic enzyme that inactivates a Signal Transducer and Activator Transcription 3 (STAT3) protein, leading to inhibition of leptin and insulin signalling. This protein can be a target for development of anti-obesity drugs. This study aimed to identify Indonesian phytochemicals as in silico TCPTP inhibitor. This bioinformatics study used a molecular docking method with AutoDock Vina software version 1.1.2. Three-dimensional structure of TCPTP protein and its Inhibitor (XIX, standard ligand) was obtained from Protein Data Bank (PDB) database with code 1L8K and PubChem database with code 9926586. Indonesian phytochemicals in this study were registered in the HerbalDB database and met criteria of Lipinski’s rule. The three-dimensional structure of phytochemicals was obtained from PubChem National Center for Biotechnology Information (NCBI). Binding affinity and molecular conformation of selected Indonesian phytochemicals were assessed and compared to the standard ligand. PyMol version 1.3 software was used to visualize molecular docking results. Inhibitor XIX interacted with TCPTP protein at Gln125 and Thr129 residues with -6.30 kcal/mol binding affinity. Actinodaphnine and Rutacridone had lower binding affinity (-6.40 kcal / mol) than the standard ligand. Actinodaphnine interacted with the TCPTP protein at Thr129 and Asp130 residues while Rutacridone had interaction at Thr129 only. However, both phytochemicals had different conformation from PTP inhibitor XIX. Actinodaphnine is more potential to become a TCPTP inhibitor in silico for treatment of obesity than Rutacridone. Further investigation is required to evaluate the inhibitory effect of both phytochemicals towards the TCPTP protein.
Synthesis of 3-(7-triphenylphosphonioheptyl)-2,6-dimethyl-1,4-benzoquinone) and The Activity Test Toward Glycogen Phosphorylase Enzyme: In silico Approach
Authors: Furoida Andriani , Ulfa Siti Mariyah 
Published: June 2019

Abstract
The synthesis of 3-(7-triphenylphosphonioheptyl)-2,6-dimethyl-1,4-benzoquinone) (TFH) is carried out by bromoalkylation and insertion of triphenylphosphonium moiety by refluxed of 2,3-dimethyl-1,4-benzoquinone using bromooctanoic acid triphenylphosphine. The alkylation gave 17.14% yield of 2-(7-bromoheptyl)-3,5-dimethyl-1,4-benzoquinone (C7) and 3-(7-triphenylphosphonioheptyl)-2,6-dimethyl-1,4-benzoquinone) (TFH) is obtained at 40.35% yield. Structure characterization of the synthesized product was performed mainly using UV-Vis, FT-IR, and 1H-NMR. UV-Vis characterization showed maximum wavelength of TFH at 198 nm, 226 nm, and 260 nm. FT-IR characterization showed sp3 character at 2930.43 cm−1 and the disappearance of C-Br peak at 687.37 cm−1, indicates the presence of long chain alkyl group and the replacement of Br with triphenylphosphonium. In silico investigation by using Glycogen Phosphorylase enzyme as molecular target estimated IC50 value of thymoquinone, C7, and TFH, that is, 16.14 ppm, 162.2 ppm, and 1.26 ppm, respectively. Thus, TFH has the smallest IC50 value suggested that most effective drug candidate compared with thymoquinone and C7.
Correlation and Meta-Analysis of HER2 in Each Stage of Breast Cancer
Authors: Ramanto K N , Agustriawan David , Parikesit A A , Nurdiansyah Rizky , Nasution Muhammad Z A 
Published: June 2019

Abstract
Human Epidermal growth Receptor 2 (HER2) plays an essential role in the pathogenesis of breast cancer. Previous studies have shown that HER 2 overexpression is associated with a higher histological tumor grade. Furthermore, the overexpression of HER 2 is associated with miRNAs expression. However, the interaction of HER2 and miRNAs in each stage of breast cancer remain unclear. The objective of this study is to identify the relationship between HER2 and miRNAs expression in each stage of breast cancer. Thirteen miRNAs were selected based on literature evidence that showed their interaction with the overexpression of HER 2. The correlation and meta-analysis were done by using the R programming language. The result of this study showed hsa-mir-10b has the highest correlation value in stage two and three breast cancer. On the other hand, hsa-let-7f-2 has the highest correlation value in stage one breast cancer. The result of meta-analysis also showed a significant level of p-value (0.007). These results indicate the downregulation miRNAs only occur in a specific stage of breast cancer.
Optimization of the Hermetia illucens Larvae Extraction Process with Response Surface Modelling and Its Amino Acid Profile and Antibacterial Activity
Authors: Sholikin Mohammad Miftakhus , Alifian Mochamad Dzaky , Jayanegara Anuraga , Nahrowi  
Published: June 2019

Abstract

Hermetia illucens Larvae (HiL) is a protein source that can replace soybean meal and act as functional feed in the poultry industry. This study aims to optimize the HiL extraction process and evaluate the amino acid profile and antibacterial activity. Response surface modelling (RSM) was used to optimize the HiL extraction process and yield assessment. RSM followed by three levels and three variables based on Box-Behnken design. The extraction method used alkali extraction procedure with three variables, e.g., X1: NaOH solvent, X2: HCl solvent, and X3: precipitation volume. Inhibitory zone assay used Staphylococcus aureus, Bacillus subtilis, Salmonella typhimurium and Escherichia coli. Model build by RSM has R2 = 0.9949 with significant value (P<0.01). The correlation plot of experimental yield versus predicted yield has R2 = 0.9974. Validation of the model has a lack of fit value (P>0.05) which indicate that the model is valid. The EAAI and BV value of HiL extract are 16.51 and 5.30%, respectively. HiL extract did not show antibacterial activity to inhibit gram-positive and gram-negative bacteria. The optimum yield (23.03%) was obtained by performing with NaOH 2.35 M, HCl 2.76 M, and precipitation volume 25.28 mL. EAAI of HiL extracts is slightly higher than that of dried HiL but lower than that of soybean meal.
The Potential of Bacillus cereus S1 as an Environmentally Friendly Bioaccumulator of Gold Nanoparticle Waste
Authors: Zulaika Enny , M. Andry P. Utomo , Fitria Avip N. , Prasetyo Endry Nugroho 
Published: June 2019

Abstract
Gold (Au) is one of the metals that is widely used for jewellery and electroplating. Although in the nanoparticle form, the waste that produced still has high economic value. Since its belong to heavy metals, gold nanoparticle waste need to be removed even in the very low concentration. One of the alternatives is utilized gold-resistant bacteria, namely Bacillus cereus S1. The purpose of our study was to determine the ability of B. cereus S1 to accumulates gold. Reconfirmation test of B. cereus S1 gold resistant ability was figured out using Minimal Salt Medium (MSM), 2% glucose and 0.1 ppm gold. The bioaccumulation process was used 1 ppm, 5 ppm, and 10 ppm concentration of gold; and the incubation periods were 6, 12, and 24 hours. Gold bioaccumulation performed by B. cereus S1 was measured using Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-EOS). The results showed that the longer incubation periods of B. cereus S1, the higher gold concentration will be accumulated at exposure concentration 1 ppm, 5 ppm and 10 ppm. B. cereus S1 showed good viability after 24 hours metal exposure.
Role of Clathrin Protein to Increase Electric Current on Dye-Sensitized Solar Cell (DSSC) Based Natural Dyes
Authors: Trihutomo Prihanto , Soeparman Sudjito , Widhiyanuriyawan Denny , Yuliati Lilis 
Published: June 2019

Abstract
Dye-Sensitized Solar Cell (DSSC) has the cost of fabrication is relatively cheap, easy to produce, work on the area of the visible light and environmentally friendly. The shortage of DSSC, namely the efficiency is still low compared with solar cells of silicon. In this study, have been successfully fabricated DSSC with clathrin protein deposited. The method used in this research is to deposit clathrin protein in porous TiO2 semiconductors with a concentration of 0%, 25%, 50%, and 75%. Tests carried out on the DSSC that has been made current testing electricity using a solar simulator to determine the changes in electrical current that occur in DSSC. The conclusion from this research is that with increasing concentration of the addition of the clathrin protein in the DSSC leads to an increase in the electric current generated by DSSC. From the results of testing using a solar simulator obtained the value of electric current is the highest, namely 5.247 mA with the addition of the concentration of the clathrin protein by 75%.