bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microfluidic Paper-based Analytical Devices (µPADs) For Analysis Lead Using Naked Eye and Colorimetric Detections
Authors: Wisang Yohana Felisita , Sulistyarti Hermin , Andayani Ulfa , Sabarudin Akhmad 
Published: June 2019

Abstract
This work describes comparation two designs of a microfluidic paper-based analytical devices (µPADs) using a wax printing for fabrication of hydrophobic zones on the chromatographic paper and their application to the detection of lead in waste samples. Two different designs used in this research were distance-based method and analysis image method. Sodium rhodizonate in tartrate buffer solution (pH 2.8) solution are used as the colorimetric reagents for the direct naked eyed detection of lead(II) on µPADs. The detection of lead(II) concentration is conducted by measuring the distanceof a colored reaction product which propagate in the detection zone (design 1) and the change in color intensity on the µPADs is also used for the lead detection using ImageJ software to determine the RGB value (design 2). Related to both methods can be used to determine the concentration of lead(II) with a comparable coefficient of determination, but based on the analysis method, design one is a design that is very simple, easy, fast, inexpensive and only uses the naked eye for detection.
Characterization of Ba0.35Sr0.65TiO3 Made by Sol-Gel Method with X-Ray Powder Diffraction, Field Emission Scanning Electron Microscopy and Impedance Spectroscopy in Capacitor Application
Authors: Dewi Rahmi 
Published: June 2019

Abstract
A thin film of Barium Strontium Titanate (BST) of ferroelectric material of Ba0.35Sr0.65TiO3 has been made using sol-gel method and annealed at 600, 650, and 700°C in order to obtain its crystalline structure. This thin film was characterized using X-Ray Diffraction (XRD), Field Emission Scanning Electron Microscopy (FESEM) and Impedance Spectroscopy. The results of XRD characterization show a graph of intensity against angle 2θ. The XRD patterns of Ba0.35Sr0.65TiO3have many peaks and confirmed that the material of Ba0.35Sr0.65TiO3 has cubic crystalline structure and their lattice parameter is in average of 2.399Å. The results of FESEM characterization show that the thickness of thin films of Ba0.35Sr0.65TiO3 at 600, 650, and 700°C were 21.21 nm, 34.61 nm and 39.08 nm, respectively. The values of capacitance at the frequency of 100 Hz with temperature of 600, 650, and 700°C are 4.84 x 10−11F, 5.24 x 10−11F and 5.61 x 10−11F, respectively. The dielectric constant of the thin films of BST at the frequency of 100 Hz with temperature of 600, 650, and 700°C are 5.47, 5.90 and 6.28, respectively. While the loss of dielectric values of the thin films of BST at 100 Hz with temperature of 600, 650, and 700°C are 0.03, 0.08 and 0.12, respectively. The result of characterization by Impedance Spectroscopy shows that the higher the frequency, the smaller complex capacitance, dielectric constant and dielectric loss. Generally, the higher annealed temperature, the higher complex capacitance and dielectric constant.
Performance of Bimetallic Fe and Co Catalyst Supported on HZSM-5 for Fischer-Tropsch Synthesis
Authors: Ihsanti D H , Jimmy  , Kurniawansyah Firman , Suprapto  , Roesyadi A 
Published: June 2019

Abstract
Fischer-Tropsch synthesis is a polymerization reaction which produces various products such as paraffin, olefins, alcohols, and aldehydes. The purpose of this study was to determine the performance of Fe and Co bimetallic catalysts with the support of HZSM-5 for Fischer-Tropsch synthesis. This study consists of two stages. The first stage was started by making a mesopore sized HZSM-5 catalyst through desilication, then impregnated with bimetallic Fe and Co which acted as a promoter. The impregnation method used was the incipient wetness impregnation. In the impregnation, process variations were made in the ratio of Fe to Co 1:9 and 2:8 metal loading was 10%. The Fe-Co catalyst / HZSM-5 was analyzed for characterization and activity tests. The characteristic tests were BET, XRD, FTIR, and EDX. The second stage was activity test of Fe-Co / HZSM-5 catalyst in the biofuel production process from syngas through Fischer-Tropsch reaction: The best performance catalyst was used for the biofuel production process. Fischer-Tropsch process was carried out in a fixed bed reactor, with an operating temperature of 200, 225, 250 °C carried out for 100 hours in one run, then analysis of product composition by GC-MS.
Polystyrene Micro-pools Distribution on Quartz Crystal Microbalance (QCM) Surface using Ultrasonic Atomization Spray Coating
Authors: Nuha S A , Khusnah N F , Kamasi D D , Sakti Setyawan P 
Published: June 2019

Abstract
Surface morphology of polystyrene thin film is one of the significant factors to be take into account in the development of quartz crystal microbalance (QCM) as biosensor and chemical sensor. Many coating methods were developed to modify the morphology of polystyrene thin film surface. Our previous study showed that ultrasonic atomization spray coating (UASC) is a promised coating method to produce a rough polystyrene thin film on QCM sensor with patterns called micro-pools. There are many parameters that can affect the uniformity of micro-pools produced by UASC. In this work, 0.5% polystyrene solution which was solved in toluene was used as material coated onto a QCM sensor using UASC method. The effect of the distance variation between the spray nozzle and specimen towards the surface morphology of polystyrene thin film was observed. The surface morphology of the coated polystyrene and the micro-pools distribution were characterized by an optical microscope and Scanning Electron Microscope (SEM). The electrical impedance of the QCM was measured and characterized using Impedance Analyzer. The result showed that the optimum distance of the spray nozzle and specimen is between the range of 15 until 24 cm. At this optimum distance, the uniform micro-pools distribution was formed on the QCM surface without influencing the QCM acoustic impedance.
Antibacterial Activity and Phytochemical Content of Silage Juice from Tropical Herbal Leaves
Authors: Prihambodo T R , Nahrowi  , Jayanegara Anuraga 
Published: June 2019

AbstractThe objective of the present study was to evaluate silage juice from tropical herbal leaves from Indonesia, namelyCordyline terminalis, Polyscias scutellaria, Cosmos caudatus, Hibiscus tileaceus, Syzygium aqueumandSwietenia mahagoniagainst pathogenic bacteria based on phytochemical content and lactic acid bacteria. This study consisted of two phases, the first phase was to explore 6 tropical herbal leavesin combination with maizecrop in making silage juice, whereas the second phase was the evaluation of 2 types of selected silage juices with different harvesting times. Parameters measured were consisted of lactic acid bacteria population, phytochemical screening qualitatively, tannin, phenolic, flavonoid contents and its ability to inhibit pathogenic bacteria, i.e.,Eschericia coliandSalmonella thypimurium.Data were analyzed by description test with table as the result. Results showed that from 6 silage juice from tropical herbal leaves, it was taken 2 best leaves based on phytochemical content and total lactic acid bacteria, those wereCordyline terminalisandPolyscias scutellaria. Result of second phase research showedCordyline terminalishad better phytochemical content thanPolyscias scutellariaso its ability to inhibit pathogenic bacteria was bigger. It is concluded thatCordyline terminalisandPolyscias scutellariawere the best combination of silage juice due to their ability to inhibit pathogenic bacteria.
Effect of Acetone/Isopropanol as Solvent TiO2 Active Flux on Penetration Characteristics Activated Tungsten Inert Gas Welding Incoloy 825
Authors: Sadewo A P , Ardhyananta H , Purniawan A 
Published: June 2019

Abstract
The purpose of this study was to investigate the effect of flux solvent on the depth-to-width ratio (DWR), microstructure, and the hardness of Incoloy 825 with activated tungsten inert gas (A-TIG) welding process. Effect of solvents on active flux of TIG welding for geometry characteristics were investigated by metallographic and defense tests. The arc constriction and Marangoni convection are considered as the two main factors for increasing the penetration of the A-TIG weld pool. Marangoni convection provided change to fluid flow in the anode area of welding it formed a thermionic electron condition because of the large positive ion collisions in the welding arc. This study investigated the effect of acetone/isopropanol as a TiO2 active flux solvents on A-TIG incoloy 825 autogenous welding. Metallography observations carried out give the best results on the addition solvents of 40% isopropanol can provide DWR 0.549 while 100% acetone solvent has DWR 0.321 and for 100% isopropanol solvent has a much smaller DWR which is 0.276. In addition to providing penetration rates, this isopropanol have an effect increasing of hardness especially in the fusion line at 40% isopropanol 198.79 HV and 100% isopropanol 202.52 HV.
Facile Synthesis of Lycopene Reduced Graphene Oxide in Different Solvent Polarity
Authors: Sugianto Wildatus Sa’diyah , Nitami Diyah , Ulfa Siti Mariyah 
Published: June 2019

Abstract
Graphene is a two-dimensional carbon which has many applications. Due to high utilities of graphene, the synthetic procedures should be developed to increase its production. The synthesis of reduced graphene oxide (rGO) using lycopene were carried out in the presence of polar and non-polar solvent. The lycopene was extracted from watermelon by solid-liquid extractionusing n-hexane/acetone/ethanol in 2:1:1 (v/v/v) and gave 5 mg/g of watermelon. The reduction of GO was performed by dissolved 100 mg of GO in 50 mL deionized water followed by sonication for 120 min, then added with 15 mL of 37 mM lycopene, reflux for 3-24 h in hexane/water and acetone/water in 3:10 (v/v) ratio, respectively. The result showed that the reaction using acetone/water in 3 h produce rGO. Replacing the solvent into hexane/water and reacted for 24 h produce rGO with similar characteristic. FT-IR analyses showed typical absorption of C = C alkenes at 1651 cm−1. The XRD showed 2-tetha at 21.5° that indicate a typical peak of rGO. The UV-Vis analysis revealed a maximum wavelength that shifted from 231-271 nm. All characteristic of the synthesized rGO showed that lycopene can be used as natural reductor for rGO synthesis.
The Effect of Precursors Concentration on the Structural Properties of MoS2Nanosheet-Microsphere Synthesized Via Hydrothermal Route
Authors: Waskito I S , Kurniawan B , Amal M I , Hanifuddin M 
Published: June 2019

AbstractMoS2nanosheet-microsphere was successfully synthesized via hydrothermal route by applying precursor of ammonium heptamolybdate and thiourea. The precursor concentration was varied of 0.25 M, 0.5 M, 1.0 M and 1.5 M. The crystal structure, morphology and particle size of as-synthesized MoS2were observed as the effect of the precursors concentration. MoS2nanosheet-microspheres were prepared inside the hydrothermal autoclave at 200 °C for 24 hours. The X-ray diffraction (XRD) characterization result showed the structure of hexagonal 2H-MoS2crystals in the absence of other secondary phase. XRD characterization results also revealed that MoS2with a precursor concentration of 0.25 M has better crystallinity in 002 plane compared to MoS2synthesized with other precursor concentrations. The Scanning Electron Microscopy (SEM) observation indicated the shape of nanosheets with a thickness of several tens nanometers which were assembled to form microsphere. SEM result also showed precursor concentrations of 0.25M to 1.5M affects to the formation of nanosheet-microsphere MoS2particle in which along the increasing of the precursor concentration the nanosheet-microsphere particle not all well-formed. Particle Size Analyzer result showed the average particle size decreased and the average specific surface area increased with increasing precursor concentration.
Optical Constant Determination of Crosslinked Chitosan-Polyethylene Glycol (PEG) using Attenuated Total Reflection Method by Surface Plasmon Resonance Phenomenon
Authors: Yahya I M , Wardani D P , Suharyadi E 
Published: June 2019

Abstract
Application of chitosan as a sensing layer for heavy metal ions in surface plasmon resonance (SPR)-based sensor with Kretschmann configuration has been done extensively using polypyrrole and gruteraldehid. The deposition methods that are very widely used in depositing chitosan onto the sensing surface are spin coating, electrodeposition and dip coating (for SPR based fiber optic sensor). The deposition technique of chitosan-polyethylene glycol (PEG) composite material as sensing layer in SPR based sensor by using the drop-casting method has not been done to the best of our knowledge. In order to use chitosan-PEG composite material as a sensing layer for heavy metal ion detection, it is necessary to determine the optical constant of chitosan-PEG which is deposited by the drop-casting method. The refractive index of chitosan-PEG with mass composition 0.4 grams chitosan and 0.04 grams PEG was determined by attenuated total reflection (ATR) method by utilizing surface plasmon resonance phenomenon on the prism/silver/chitosan-PEG interfaces in Kretschmann configuration. The refractive index then was extracted from the ATR curve by using Winspall software. Based on the experimental result, it was found that the ATR curve was shifted from 44.3° to 68.9° with the presence of a chitosan-PEG layer deposited onto the silver surface, about 0.01 ml in solution form. From the fitting result, it was found that the refractive index of chitosan-PEG was n = 1.32.
Modelling one-dimensional crystal by using harmonic oscillator potential
Authors: Abdurrouf  , Nurhuda M. , Wiyono  
Published: June 2019

Abstract
Our recent developed filter method (Phys. Rev E
96(3), 033302, 2017) is applied here to investigate the energy spectrum and their corresponding wave function of one dimensional crystal. The periodic one dimensional potential is modelled by using one dimensional periodic harmonic oscillator, with variation on oscillator potential depth, quasi-potential depth, and crystal width. For energy less than the potential depth of the oscillator, the computational results reveal that the periodic harmonic oscillator produces a discrete spectrum, as the energy spectrum of a single harmonic potential. However, for energy almost equal to or greater than the depth of the potential oscillator, the periodic harmonic oscillator demonstrates the existence of pattern similar to energy band in crystal.
Modelling of Hypertension Risk Factors Using Penalized Spline to Prevent Hypertension in Indonesia
Authors: Adiwati Tati , Chamidah Nur 
Published: June 2019

Abstract
Hypertension is an increase in blood pressure that increases to a target organ, such as stroke, coronary heart disease, right ventricular hypertrophy. Hypertension occurs if the blood pressure reaches 140 mmHg or more and diastole reaches 90 mmHg or more. According to WHO, from 50% of hypertensive patients recovering, only 25% received treatment, and only 12.5% could be treated well. Nationally, 25.8% of Indonesia’s population suffers from hypertension. In this study, we modeled the risk of hypertension by considering age, heart rate, family hypertension, stress levels, and the body’s future index as factors that influence the risk of hypertension. The cross-sectional survey was conducted in August 2018 at the Surabaya Hajj Hospital. Based on previous research the method used is logit and gompit logistic regression method, but the results obtained are not maximal. Therefore, in this study the researchers proposed a method for constructing hypertension risk factor modeling using a nonparametric application using a penalized spline estimator. The result of classification accuracy by using non-parametrical is 96%. Based on the result, we conclude that non-parametrical approach has better than outcome so that it can be used to modelling the risk of hypertension.
Grey Wolf Optimizer for Parameter Estimation of Enzymatic Reaction in Biodiesel Synthesis
Authors: Anam Syaiful , Kumaralalita Indira 
Published: June 2019

Abstract
Computational models are used to help us to understand the mechanisms of a complex process in nature. Before building the model, we need to know the characteristic of samples which are described in the form of measure named parameters. Usually, the value of parameters is unknown and we need to investigate those value to know the compatibility between the artificial model and real circumstances. Many optimization methods have been introduced to estimate those parameters, but some of them meet the difficulties caused by the nonlinear type of function model. Many objective functions of the estimation parameter are multimodal, high dimensional, and have many local optima, so the estimation process using traditional optimization method is not suggested. In this article, we use Grey Wolf Optimizer (GWO), as one of the metaheuristic artificial intelligence algorithm, which is inspired by leadership hierarchy and hunting behavior of a pack of wolves. GWO is applied to estimate the parameters in a model of enzymatic reaction in biodiesel synthesis. Biodiesel is renewable fuel that can solve the energy crisis and pollution. While the process of biodiesel synthesis occurs, some enzyme in the biodiesel substances react to each other and it can be modeled into ODEs (Ordinary Differential Equations) system. The kinetic parameters inside them are needed to be estimated. After the parameter are estimated, the fourth-order Runge-Kutta method is used to solve the system. The result is evaluated by analyzing the objective function which minimizes the Sum of Squared Errors (SSE). The small value of SSE and the narrow range of both parameter of model and estimation shows that GWO is effective to be the proposed method for parameter estimation and model selection problems.
Modelling of Income Inequality in East Java Using Geographically Weighted Panel Regression
Authors: Chotimah Chusnul , Sutikno  , Setiawan  
Published: June 2019

Abstract
Regression analysis is one of the statistical methods that study the relationship between response variables and predictor variables. Parameter estimates in classical linear regression produce regression coefficients that are thought to apply globally to the entire observation unit. But in fact, the existence of factors from the spatial aspect causes conditions between one location and another to be different. This spatial aspect allows the emergence of spatial heterogeneity. Geographically Weighted Regression (GWR) is a local development regression technique from ordinary regression using spatial data. In addition, in a study data is needed in a certain period of time involving cross-section data and time series or referred to as panel data. Geographically Weighted Panel Regression (GWPR) is a combination of GWR and panel data regression. The purpose of this study is to model Geographically Weighted Panel Regression using Fixed Effect Model (FEM) within estimators with adaptive bisquare kernel weight for data on income inequality (Gini ratio) in East Java Province from 2010 to 2014. In addition, to obtain factors that influence significant income inequality in each district/city of East Java Province. The results of this study indicate that the GWPR fixed effect model differs significantly in the panel data regression model, and the models produced for each location will be different from each other. Districts/cities in East Java Province have twenty-eight groups based on significant variables. The variables that significantly influences income inequality are the percentage of the poor, percentage of GDP regional in the category of fisheries forestry agriculture, percentage of GDP regional in the processing industry category, percentage of GDP regional gross fixed capital formation, per-capita GDP regional, and dependency ratio. In the GWPR model, the R2 value is 99.953%, with Root Mean Square (RMSE) is 0.0061035. While the FEM model within estimator produces an R2 value of 22.844% with RMSE is 0.1035616.
Simulation on the Zero Inflated Negative Binomial (ZINB) to Model Overdispersed, Poisson Distributed Data
Authors: Fitriani Rahma , Chrisdiana Lidia Novita , Efendi Achmad 
Published: June 2019

Abstract
Poisson regression analysis shows the relationship between predictor variables and response variables that follow the Poisson distribution which has equal dispersion and average values (λ), a situation called equidispersion. However, the variance can also be greater than the average value, called overdispersion. This can be caused by excess opportunities for the emergence of zero values in the response variable or zero excess. The parameter of the overdispersed data analysis can be underestimated so that the results become biased. This bias issue can be, hopefully, overcome by the Zero Inflated Negative Binomial (ZINB) regression analysis. In the 2016 Maternal Mortality Rate data in Bojonegoro District, overdipersion was overcome by ZINB regression even though there was no significant predictor variable found affecting the response variable. ZINB regression analysis can also be applied to generated data (simulation). We had the data with average λ = (0.2, 0.4, 0.6, 0.8, 1.0, 5.0) proportion of zeros p = (0.4, 0.6, 0.8), and the number of observationsn = (200,500, 800), with each setting was repeated 100 times. From the simulation study it was found that all overdispersion events were always accompanied by zero excess events but not vice versa. The greater the value of λ then the greater the dispersion coefficient. The ZINB regression is proven to be able to overcome overdispersion in various conditions of different values of λ, p, n which can be seen from the value τ (dispersion coefficient) after ZINB regression is less than 1 in all conditions.
Kernel-Spline Estimation of Additive Nonparametric Regression Model
Authors: Hidayat Rahmat , Budiantara I Nyoman , Otok Bambang Widjanarko , Ratnasari Vita 
Published: June 2019

Abstract
In this paper, we model the open unemployment rate with the Kernel-Spline model. We investigate and compare the performance of model Kernel-Spline by varying the Kernel function. The performance model has been compared with five Kernel function i.e. Kernel functions Uniform, Epanechnikov, Quartic, Gaussian, and Triweight. For these models, we conducted a comparison based on actual data sets, the unemployment rate in East Java. The best model was chosen based on the Generalized Cross Validation value and the coefficient of determination criteria. The empirical results obtained have shown that Spline-Kernel model by using the Gaussian Kernel better than other models.
Feature Selection using Random Forest Classifier for Predicting Prostate Cancer
Authors: Huljanah Mia , Rustam Zuherman , Utama Suarsih , Siswantining Titin 
Published: June 2019

Abstract
Prostate cancer is cancer that attacks the prostate gland, usually affecting men over 50 years. Prostate cancer is a disease that develops slowly. Based on this, rapid and precise detection is needed so that the disease can be treated immediately. This study focuses on the application Feature Selection using the Random Forest Classifier to detect prostate cancer. The Random Forest Classifier is a method of classifying data by determining the decision tree. The use of more trees will affect the accuracy to be obtained for the better. The Random Forest Classifier can classify data that has incomplete attributes and can be used to handle large sample data. Selection of features is an important process because it can affect the accuracy of classification. This method increases accuracy by about 87%. Thus, the selection of features can improve accuracy in the detection of prostate cancer.