bluuebunny/crossref_metadata_2025 huggingface dataset:
Possibility of astronomical phenomena to be used to support tourism industry
Authors: Kunjaya C , Melany  , Sukmaraga A A , Arsono T
Published: June 2019

Several astronomical events in the past have shown their potential to attract tourists. This motivates some astronomers and tourism activists to create tourism related events when an interesting astronomical phenomenon occur. The most attractive recent astronomical phenomenon for tourists was the solar eclipse as was proven during the total solar eclipse of March 9, 2016. Similarly, other phenomena such as the lunar eclipse, meteor shower, Mars Opposition have some potential to be exploited as events to attract tourists. Belitong Geopark had organized a sky observation event, for example super blue blood moon event on January 31, 2018 and Mars opposition event on July 21, 2018. It successfully drew attention far and wide, but it needed more effort and creativity to make these events more attractive and marketable. Other cultural heritage sites which contain inherent astronomical tie-in knowledge, such as Borobudur Temple, are also strong prospective to be developed for astro-tourism destinations. In the future, astro-tourism permanent facilities may be developed, for example, sky observation facilities for amateurs in Dark Sky National Park, near Mount Timau National Observatory in Kupang, East Nusa Tenggara Province.
Constraints on the total mass and mass hierarchy of neutrinos from cosmological observations with bayesian analysis
Authors: Emas N P A P , Wulandari H
Published: June 2019

In the standard model neutrinos consist of three species (flavors) and are massless. However, solar neutrino problem that was solved by neutrino oscillations requires that neutrinos have non-zero masses. Another support for non-zero neutrino masses comes from kinematic experiments. Oscillation experiments give rise to a further problem regarding the order of neutrino masses, known as the neutrino mass hierarchy problem, i.e. whether the hierarchy is normal or inverted. On cosmological scales, massive neutrinos affect Cosmic Microwave Background (CMB) and Large Scale Structure (LSS) formation. The impact of massive neutrinos is imprinted in the power spectrum of CMB, and in the LSS matter power spectrum as well. Since neutrinos affect events in the universe, it is possible to constrain neutrino properties based on cosmological observations. This work is aiming at constraining neutrino total mass from cosmological observations in the two hierarchy scenarios, i.e. normal and inverted hierarchies, and also at determining which neutrino mass hierarchy is favoured by cosmological observations. To constrain neutrino total mass we employed CosmoMC and performed Bayesian analysis with MCMC algorithm, while neutrino mass hierarchy was determined based on Bayes factors, in which likelihoods of the two hierarchy scenarios were compared. In addition, neutrino individual masses were estimated by combining results of oscillation experiments. Depending on the dataset used, different total mass constraints were obtained. The tightest constraint comes from a combination of CMB + LSS + BAO + Supernova data, i.e. Σmv
< 0.183 eV (normal hierarchy) and Σmv
< 0.188 eV (inverted hierarchy) with 95% C.L. The Bayes factors analysis prefers normal hierarchy, although with weak evidence.
Loop Quantum Gravity treatment of Charged Black Hole Thermodynamics
Authors: Daas Tirtho
Published: June 2019

This paper aims specifically at answering two contemporary requirements of a quantum theory of gravity, shown by using Loop Quantum Gravity (LQG) theory on the mathematics of black hole thermodynamics by (i) to quantise known classical General Relativistic formulations of black holes using LQG; and (ii) using LQG microstate spacelike sections (holonomies) on established quantum formulations of general relativity like Generalised Uncertainty Principle, to advocate for background independence in the mathematics of black hole horizon as the next step towards a viable quantum theory of gravity.
Identifying changing precipitation extremes in Sub-Saharan Africa with gauge and satellite products
Authors: Harrison Laura , Funk Chris , Peterson Pete
Published: June 2019

Sparse gauge networks in Sub-Saharan Africa (SSA) limit our ability to identify changing precipitation extremes with in situ observations. Given the potential for satellite and satellite-gauge precipitation products to help, we investigate how daily gridded gauge and satellite products compare for seven core climate change precipitation indices. According to a new gauge-only product, the Rainfall Estimates on a Gridded Network (REGEN), there were notable changes in SSA precipitation characteristics between 1950 and 2013 in well-gauged areas. We examine these trends and how these vary for wet, intermediate, and dry areas. For a 31 year period of overlap, we compare REGEN data, other gridded products and three satellite products. Then for 1998–2013, we compare a set of 12 satellite products. Finally, we compare spatial patterns of 1983–2013 trends across all of SSA. Robust 1950–2013 trends indicate that in well-gauged areas extreme events became wetter, particularly in wet areas. Annual totals decreased due to fewer rain days. Between 1983 and 2013 there were positive trends in average precipitation intensity and annual maximum 1 d totals. These trends only represent 15% of SSA, however, and only one tenth of the main wet areas. Unfortunately, gauge and satellite products do not provide consensus for wet area trends. A promising result for identifying regional changes is that numerous satellite products do well at interannual variations in precipitation totals and number of rain days, even as well as some gauge-only products. Products are less accurate for dry spell length and average intensity and least accurate for annual maximum 1 d totals. Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (3B42-V7) and Climate Hazards center Infrared Precipitation with Stations (CHIRPS v2.0) ranked highest for multiple indices. Several products have seemingly unrealistic trends outside of the well-gauged areas that may be due to influence of non-stationary systematic biases. Social media abstract. Sparse data show increasing Africa rainfall extremes and satellite products fill some missing pieces.
Employment of hyper-cycloidal oscillatory motion for finding the coefficient of rolling friction. Part 2: Experimental investigation
Authors: Ciornei F C , Pentiuc R-D , Alaci S , Romanu I C , Irimescu L , Buium F
Published: June 2019

The paper presents a method for finding the characteristics of rolling friction between two cylindrical external surfaces. By choosing the motion between two parallel cylinders it results that a point from one of the cylinders describes a hyper-cycloidal curve when rolling over the other cylinder. The study is focused on the friction in ball bearings. Parts of the ball bearings to be studied are directly involved in materializing the hyper-cycloidal contact. Thus, the immobile circles are materialized by the outer surface of the external ring and the mobile circles are materialized by the spherical surfaces of the balls. The motion of a laser stick attached to the pendulum is filmed. Analyzing the movie, the numerical time dependence of angular amplitude decrease is obtained. The concordance between the experimental and theoretical angular amplitude damping directs to the value of coefficient of rolling friction.
Some aspects regarding the roughness of the railway surface and rolling noise at locomotives
Authors: Babici L M , Tudor A
Published: June 2019

Railway noise is activated by irregularities on the running surfaces of rails and wheels, these being more significant for the most part of the wavelength and the frequency range of interest. The rolling noise generation mechanism consists of two major structural components: the wheel and rail. The contribution to the noise of the track can be further separated into noise radiation on the rails and in the sleepers. To mitigate the rolling noise, these components must be analysed. To direct and manage mitigation methods within Faurei Railway Testing Center, the rail surface roughness in accordance with EN 15610 was determined in a line of alignment, this being a direct method of measuring the surface roughness of the rail, in association with the rolling noise introduction. In this paper, it is proposed a fractal analysis of the microgeometry of the rail surface, with the possibility of using it as an acoustic parameter.
Simulation of Charpy test for different impact velocities
Authors: Musteață A E , Pirvu C , Deleanu L , Georgescu C
Published: June 2019

This paper presents how a finite element model of Charpy sample fails when it is hit with an impactor. Studying the step-by-step evolution of failure of polymeric sample allows for establishing stages of the process characterising the Charpy impact, pointing out processes and phenomena that are difficult to be noticed during the actual impact or by investigating the broken pieces. The simulation was run for different impact velocities (1…3 m/s) and the sample material was considered a bilinear orthotropic hardening model. After analysing the images of the simulations, the following conclusions may be formulated. Simulation helps identifying the stages of the material failure. Using the bilinear hardening model for the polymer failure at low impact velocity (1…3 m/s) gave reasonable simulations. The time for failure process is longer at lower speed and the aspect of the failed surface depends on the impact velocity.
The state of the modular element structure of a prehensor through virtual prototyping
Authors: Frincu I C , Stroe I
Published: June 2019

The paper presents the study of the geometric scheme of the structure of a prehensor module. The prehensor has the role of generating the force required to manipulate an object respecting the prehensor’s plan with the manipulated object. It is proposed the static concept of the prehensor according to the geometric parameters of the prehensat object. Starting from the structural scheme of the proposed module, the 3D component structure is generated using the Catia software. The kinematics of the studied structure is presented and the system modeling prerequisites are created through the Adams program. Importing the system into Adams simulates the kinematics of the proposed structure. The state of stresses and deformations of the prehensor module is determined and presented. The prehensor module of this type is designed for the reliability of the prehensor.
Kinematic Modelling of Contact Point between Chain Bush and Sprocket
Authors: Velicu R , Săulescu R , Gavrilă C C
Published: June 2019

As is well known, in the automotive industry there is a tendency to obtain the most efficient, reliable and compact systems. Because the belt drives used are subject to excessive elongation and wear in most applications, since high performance engines are desired, distribution chains are preferred. The dynamic behavior of a chain drive during operation is directly influenced by its geometry and, implicitly, by the chain contact with the sprocket. Since the application of normal and transverse forces occurring in a chain transmission depends directly on their application point and thus on the point of contact between the chain and the sprocket, the kinematic modeling of the point of contact between the chain bushings and the sprocket is proposed in present paper.
Dynamic optimization of a dual-axis solar tracker for PV modules
Authors: Marcu A , Alexandru C , Barbu I
Published: June 2019

This paper deals with the dynamic optimization of the dual-axis tracking mechanism, which is used for increasing the energetic efficiency of a photovoltaic module, by maximizing the rate of incident solar radiation. The study is based on the optimal design algorithm included in the commercial MBS (Multi-Body Systems) software solution ADAMS, through the parameterization of the virtual model, which offers the possibility to perform a series of studies aiming at identifying the design parameters that decisively influence the dynamic behavior of the tracking systems. The global coordinates of the design points (i.e. the mounting points of the actuating sources) are defined as design variables for the optimization process, while the design objectives refer to the power consumptions of the actuating sources.
High Performance Liquid Chromatography (HPLC) Method for Determination of Isoflavones Content in Shade-Tolerant Soybean Dena I
Authors: Daud Adawiah , Sulistyarti Hermin , Retnowati Rurini , Ginting Erliana
Published: June 2019

Soybeans (Glycine max (L.) Merrill) are the most common source of isoflavones in human foods which useful for health as preventions of cardiovascular disease, cancer, diabetes, hypertension, osteoporosis, and menopause. The amount of isoflavones in soybeans may differ significantly depends on both genetic and environmental factors. Among the four forms of isoflavones, the highest biological activity is indicated by isoflavones aglycones i.e., genistein, daidzein, and glycitein. Genistein and daidzein found as major compounds with significant amounts contained in soybeans. Indonesian Legumes and Tuber Crops Research Institute (ILETRI) cultivate a shade-tolerant soybeans variety called Dena I to overcome the production of soybeans in Indonesia. Although finding exist for Dena I variety, there are no firm data regarding the isoflavones content of this variety. In this research, high performance liquid chromatography (HPLC) method using a C-18 column with UV detection in optimum condition was performed to identify and quantify the isoflavones content in the extract of Dena I soybean. The satisfied separation was obtained using the mobile phase of acetonitrile-acetic acid 0.1% with the gradual increase of acetonitrile 15-30%, the flow rate of 1 mL/min, and detection wavelength of 260 nm. Isoflavone genistein in Dena I extract was eluted at the retention time (tR) of 24.696 min, the same way with the retention time (tR) of standard genistein of 24.490 min. The concentration of genistein was found 0.0524 mg/g Dena I soybean.
Developing a Mickey-Mouse-Designed Microfluidic Paper-Based Analytical Device (μPAD) to Determine The Antioxidant Activity of Green Tea
Authors: Fauziyah Na’ilah , Andini  , Anneke  , Oktavia Ika , Sari Meiria Istiana , Sulistyarti Hermin , Sabarudin Akhmad
Published: June 2019

The determination of the antioxidant activity in green tea using FRAP essays developed in a Microfluidic Paper-Based Analytical Device (μPADs) was observed. μPAD was prepared on the chromatographic paper with a suitable pattern and then printed using a solid ink printer. The solid printing was intended to obtain a hydrophobic barrier and a hydrophilic channel on the chromatographic paper. A preliminary study was done to determine the optimum time and temperature used on the penetration of obtaining the hydrophobic barrier to avoid leakage in the channel. Optimization of temperature and time was calculated by the average velocity, the optimum condition was obtained at 120 °C for 90 seconds with an average speed of 0.1 mm.s−1. The green tea samples were prepared by extracting its active compound using demineralized water at 25 °C and 90 °C with 2 hours of immersion time. For the measurement of antioxidant activities, the analysis was carried out by placing 0.5 μl in the detection zone and 5 μl samples into the sample zone μPAD. Then, the color reaction product, which propagates from the sample zone to the detection zone, is processed by Image J software to measure color intensity in CMYK mode. Extracts of green tea samples at 25 °C and 90 °C has a significant difference in antioxidant activity. These results indicate that the method developed in this work can be used as an alternative method for analyzing antioxidant activity in green tea extract. The results of the average amount of antioxidant activity in green tea samples were shown with Fe2+ concentration. High-speed detection, low cost, high accuracy, and ease of use can be attributed to the advantages of our μPAD method.
Sequential Injection Analysis for Determination of Lead(II) using Extract of Caesalpinia Pulcherrima as a Natural Reagent
Authors: Sabarudin Akhmad , Indrayani Devi Oktavia
Published: June 2019

The lead(II)-contaminated aquatic environment may endanger humans and living organism. The maximum tolerable limit of lead(II) in river water is 1 mg/L. Therefore, the development of a sensitive and green analytical method to determine lead(II) is required. In this work, we developed a Sequential Injection Analysis (SIA) system equipped with a valve-mixing and a flow-based UV detector for highly sensitive detection of lead(II). In order to deal with the green chemistry system, the environmentally friendly natural reagent is prepared from the extract of Caesalpinia pulcherrima instead of a commercial synthetic reagent. The extract of Caesalpinia pulcherrima contains several flavonoid compounds which can bind lead(II) ion to form an orange complex compound at a wavelength of 672.4 nm. Various parameters affecting the sensitivity of the proposed method, which includes pH, reaction time, the flow rate to the detector, and stability of Caesalpinia pulcherrima extract, were investigated in detail. The optimum conditions for a complex formation of Pb-Caesalpinia pilcherrima extract were found at pH 4 along with a reaction time of 10s, and the product flow rate to the detector was 200 µL/s. Under the optimum conditions, a linear calibration graph can be constructed in the lead(II) concentration range of 0-800 ppb with a detection limit of 8.9 ppb. The proposed method is successfully applied to determine lead(II) in industrial wastewater samples with satisfied results.
Numerical Solution of Nonlinear Vibration by Euler-Cromer Method
Authors: Saroja Gancang , Nuriyah Lailatin
Published: June 2019

Nonlinear equations are able to present many behaviours of physical systems better than linear equations. Analytical solutions to nonlinear vibration equations have intractability characteristics, while limitations in computational software resources make it difficult to study systematically the phenomena in many systems. In this paper, the Euler-Cromer method is used to solve numerically the vibration equation nonlinear. The nonlinear vibrations of the equation of harmonic, Van der Pol, and Duffing oscillator motion are used as the physical case models to solve. Simulation results show that the Euler-Cromer method provides a numerical solution that is easy to implement and accurate.
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

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

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

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

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

The 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

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

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

MoS2nanosheet-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

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

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

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

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

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

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

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

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.
Analyzing Netizens’ Perceptions Towards Indonesian Presidential Candidates Using Topic Modeling Approach
Authors: Karolita Devi , Lestari Ariesta
Published: June 2019

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

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

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.