bluuebunny/crossref_metadata_2025 huggingface dataset:
From in vitro to ex vivo: subcellular localization and uptake of graphene quantum dots into solid tumors
Authors: Kersting David , Fasbender Stefan , Pilch Rabea , Kurth Jennifer , Franken André , Ludescher Marina , Naskou Johanna , Hallenberger Angelika , Gall Charlotte von , Mohr Corinna J , Lukowski Robert , Raba Katharina , Jaschinski Sandra , Esposito Irene , Fischer Johannes C , Fehm Tanja , Niederacher Dieter , Neubauer Hans , Heinzel Thomas
Published: June 2019

Among various nanoparticles tested for pharmacological applications over the recent years, graphene quantum dots (GQDs) seem to be promising candidates for the construction of drug delivery systems due to their superior biophysical and biochemical properties. The subcellular fate of incorporated nanomaterial is decisive for transporting pharmaceuticals into target cells. Therefore a detailed characterization of the uptake of GQDs into different breast cancer models was performed. The demonstrated accumulation inside the endolysosomal system might be the reason for the particles’ low toxicity, but has to be overcome for cytosolic or nuclear drug delivery. Furthermore, the penetration of GQDs into precision-cut mammary tumor slices was studied. These constitute a far closer to reality model system than monoclonal cell lines. The constant uptake into the depth of the tissue slices underlines the systems’ potential for drug delivery into solid tumors.
Voltage waveform tailoring in radio frequency plasmas for surface charge neutralization inside etch trenches
Authors: Krüger Florian , Wilczek Sebastian , Mussenbrock Thomas , Schulze Julian
Published: June 2019

The etching of sub micrometer high-aspect-ratio (HAR) features into dielectric materials in low pressure radio frequency technological plasmas is limited by the accumulation of positive surface charges inside etch trenches. These are, at least partially, caused by highly energetic positive ions that are accelerated by the sheath electric field to high velocities perpendicular to the wafer. In contrast to these anisotropic ions, thermal electrons typically reach the electrode only during the sheath collapse and cannot penetrate deeply into HAR features to compensate the positive surface charges. This problem causes significant reductions of the etch rate and leads to deformations of the features due to ion deflection, i.e. the aspect ratio is limited. Here, we demonstrate that voltage waveform tailoring can be used to generate electric field reversals adjacent to the wafer during sheath collapse to accelerate electrons towards the electrode to allow them to penetrate deeply into HAR etch features to compensate positive surface charges and to overcome this process limitation. Based on 1D3V particle-in-cell/Monte Carlo collision simulations of a capacitively coupled plasma operated in argon at 1 Pa, we study the effects of changing the shape, peak-to-peak voltage, and harmonics’ frequencies of the driving voltage waveform on this electric field reversal as well as on the electron velocity and angular distribution function at the wafer. We find that the angle of incidence of electrons relative to the surface normal at the wafer can be strongly reduced and the electron velocity perpendicular to the wafer can be significantly increased by choosing the driving voltage waveform in a way that ensures a fast and short sheath collapse. This is caused by the requirement of flux compensation of electrons and ions at the electrode on time average in the presence of a short and steep sheath collapse.
Preliminary study on relation between temperature, humidity and Night Sky Brightness in Yogyakarta
Authors: Pramudya Y , Budi K S , Okimustava  , Muchlas
Published: June 2019

The meteorological data is important to be collected especially at the observatory. Temperature and humidity are two parameters that can be monitored as part of meteorological data collections. The observatory site also need to be protected from light pollution. The light pollution level is usually measured by the value of Night Sky Brightness (NSB). In this paper, the relation between temperature, humidity and NSB will be studied. The temperature and humidity were measured by DHT11 Sensor that is assembled and monitored using Internet of Thing method. The NSB was measured using Sky Quality Meter. The measurements have been done in Observatorium UAD, Yogyakarta. The correlation calculation was employed to perform relationship analysis. The correlation value of temperature on NSB are in the range of -0.767 to 0.576. Hence, there is no particular pattern for the relationship between temperature and NSB. The correlation value of humidity on NSB are in the range of -0.812 to 0.977. Here, the humidity tend to have more number positive relationship to NSB. As the humidity increased, the NSB is increasing. However, the investigation on temperature and humidity data changes in particular duration of time measurement will give complete information about the relationship between temperature, humidity, and NSB. The conclusion can be used to create prediction model of NSB monitoring system.
Optical spectroscopy of nova ASASSN-17hx at Bosscha Observatory
Authors: Adhyaqsa A , Istiqomah A N , Ramadhan D G , Imaduddin I , Malasan H L , Arai A , Kawakita H
Published: June 2019

We report optical spectroscopic observations in 2017 at Bosscha Observatory on an interesting nova, ASASSN-17hx (Nova Sct 2017). The nova ASASSN-17hx was observed on July 26th, July 29th, July 31st, and August 14th. Based on the light curve, we propose that our spectroscopic observation of ASASSN-17hx was conducted during “iron curtain” phase. The observed spectra showed a strong Hα emission line and multiple emission lines of Fe II multiplets, which is typical for a Fe II type nova. However, since ASASSN-17hx was classified as a He/N type only few days after its outburst, it is suggested that the nova is actually a hybrid type nova. We will discuss the characteristic of ASASSN-17hx by analysing its expansion velocity, electron density, and evolution of the emission lines.
Applying Deep Neural Networks (DNN) for Measuring Photometric Redshifts from Galaxy Images: Preliminary Study
Authors: Syarifudin M R I , Hakim M I , Arifyanto M I
Published: June 2019

In the cosmological and extragalactic study, distance to a galaxy is an important parameter, by knowing the distance, we can find any other physical parameter such as mass, luminosity, star formation rate, and metallicity. By applying the specific cosmological model, we can measure a distance from the redshift. The exact redshift can only measure by using the spectroscopic technique (Doppler effect), but spectroscopic observation limited to brighter objects and numbers of objects in a single field of view (FoV). While photometric observation can capture fainter objects and more objects in a single FoV. Measurements of photometric redshift could have done by comparing the SED curves of the elliptical galaxy with known spectroscopic redshifts from other elliptical galaxies which we want to find the photometric redshift. Another method is to do linear or non-linear regression, by assuming the redshift is a function of magnitude in each band-pass filter. Therefore, we propose a technique that using full galaxy images in each measured bands and machine learning method for measuring photometric redshift. We pass entire multi-band galaxy images into the machine learning architecture to get an estimated redshift. In this work, we use galaxies images at 0 ≤ z ≤ 1 from SDSS DR 10 as the datasets and we use DenseNet, one of the Deep Neural Networks (DNN) architecture.
Radial Fourier transforms in exoplanetary imaging and potential uses at Timau National Observatory
Authors: Albanna H , Doelman D , Mumtahana F
Published: June 2019

Due to Fourier transforms nature between the field detected on the image and its corresponding input, astronomical imaging can be modelled mathematically. In exoplanetary imaging, we aim to detect exoplanets whose typical contrast are approximately one over a million times dimmer compared to their parent stars. Among the possible approaches to accomplish that is optical apodization, a technique to purposely modify the input signal profile such that the ‘Airy rings’ on the resulting image are suppressed while keeping the central brightness high. In the paper, we pedagogically describe this technique applying Fourier transforms of radially-symmetric functions; and investigate potential future uses at Timau National Observatory.
Preliminary Report of Light Pollution in Indonesia Based on Sky Quality Observation
Authors: Admiranto A. G. , Priyatikanto R. , Maryam S. , Ellyyani  , Suryana N.
Published: June 2019

We observed night sky quality in several LAPAN stations (Agam, Bandung, Pontianak, Sumedang, Garut, Pasuruan, and Biak) which were conducted from April until July 2018 using Unihedron Sky Quality Meter LU-DL type. Observational data from all of the observational points were then sent regularly to a centralized database for further use. Although most of the measurements were done in overcast conditions, we were able to determine the representative clear sky brightness statistically. The results showed that the light pollution level of the most of the stations are moderate (the values at Biak, Agam, Sumedang, and Pontianak are 20.0, 19.5, 19.6, and 17.7 mpsas respectively) and the stations which are located near or in cities are high (Bandung and Pasuruan with 17.1 and 18.0 mpsas, respectively). In a particular station (Garut) the light pollution is low (20.6 mpsas), so it is good to make this spot to be a location of astrotourism.
Atmospheric drag force on LAPAN-TUBSAT during geomagnetic storm 2015
Authors: Pratiwi N , Ikhsan M I
Published: June 2019

The purposes of this research are (1) determine the relationship between LAPAN-TUBSAT orbital elements and geomagnetic activity; (2) estimate daily drag acceleration; (3) determine the relationship between drag acceleration and geomagnetic activity. We used STK (System Tool Kit), python, and CCMC (Community Coordinated Modeling Center) interactive model to process the data. To calculate the drag acceleration, it takes data of satellite’s velocity that obtained from STK and atmospheric density. To generate atmospheric density, we used CCMC with MSISE-90 (Mass Spectrometer – Incoherent Scatter Extended 1990) and IRI (International Reference Ionosphere) atmospheric model. In addition, it takes the satellite’s position (latitude, longitude, and height – taken from STK) as input. On March 2015, geomagnetic storm index (daily Dst) had a minimum value of -105 nT on March 18, 2015. According to hourly Dst data, the minimum value of Dst reached -223 nT at 23:00 UT on March 17, 2015. Changes of orbital elements were influenced by geomagnetic storms through the Dst index. Maximum changes of semi-major axis, inclination, argument of perigee, and longitude of ascending node occurred on March 17-21, 2015 (geomagnetic storm period). Minimum change of eccentricity occurred on March 15-16, 2015 when Dst reached a maximum value. Atmospheric model is influenced most by solar conditions both during periods of calm or storm. Atmospheric density generated by MSISE-90 and IRI, both of them has 10−6 order difference. MSISE-90 is 10−16 while IRI 10−22. For MSISE-90, maximum drag acceleration reached 451,4416 m/hari2 occurred on March 17, 2015, along with a strong geomagnetic storm phenomenon. For IRI, the value of drag acceleration during peak geomagnetic storm (March 18, 2015) reached 0,000373 m/hari2 (close to the minimum value in March 2015). Drag acceleration of LAPAN-TUBSAT is linear to the Dst index with a correlation coefficient of -0,51.
Evaluation of the corrosion wear speed of different equipment in the water injection treatment plant
Authors: Dudu C , Ripeanu R G , Drumeanu A C , Dinita A , Lospa A M
Published: June 2019

The paper presents the results of the theoretical and experimental researches carried out for the evaluation of the corrosive rate of different equipment from water injection treatment plant used for water flooding. The degradation are occurring mainly at pipelines and connecting elements of the flotation skid, in the form of advanced corrosion wear because the water injection contains an inconsistent composition mixture of dissolved gases, hydrocarbons, solid particles. The manifestation of corrosion wear at the skid connections indicates that the mechanical-physical-chemical treatments used to reduce aggressiveness are not sufficiently effective. The tests were carried out on the corrosion specimens taken from the critical areas of the skid connections and using the different formation water taken from the same critical points. Corrosion rate was obtained through experimental tests made in accordance with ASTM G5-15 and ASTM G1-03. The results materialized in the form of an influence of corrosion inhibitor and temperature on the corrosion rate for different formation water samples.
Nonstandard teeth profile description and justification of precessional gear parameters selection
Authors: Bostan I , Dulgheru V
Published: June 2019

Teeth profiles have an important role in the efficient transformation of motion in the precessional transmissions. Multiple precessional gear theory, previously developed, did not take into consideration the influence of the diagram error of the linking mechanism in the processing device for gear wheel on the teeth profile. Functioning under the multiplication regime, these errors have major influence, which can lead to instant blocking of gear and to power losses. With this purpose, a thorough analysis was conducted on the motion development mechanism under multiplication, and on the teeth profile error generating source. On the basis of fundamental theory of multiple precessional gear, previously developed, a new gear with modified teeth profile and the technology for its industrial manufacturing was proposed and patented. The elaboration of the mathematic model of the modified teeth profile is based integrally on the mathematic model of teeth profile, previously developed by the authors. With this purpose it is necessary to present the detailed description of teeth profile without modification and, then, to present of the description of modified profile peculiarities.
Identification and viewing of singularities for a new type of 6

R_

SS parallel mechanism
Authors: Milica L , Năstase A , Andrei G
Published: June 2019

This paper presents a method for determining the singular configurations of a 6RSS parallel mechanism based on its kinematic model. The parallel mechanism consists of a fixed plate and a mobile platform connected through six independent kinematic chains. Each of the six kinematic chains has an actuating rotational joint and two spherical joints. The kinematic analysis is based on the kinematic screw method. The resultant motion can thus be represented by composing the kinematic screws of the component motions. Starting from the two Jacobian matrices of the kinematic model, the two types of singularities encountered in parallel mechanisms are identified. Singular configurations are determined by an algorithm which is further used to produce three-dimensional representations of the two matrices determinants. Also, with the same program, it is possible to accurately establish the existence or inexistence of a mechanism for a given position and orientation.
Command and Control vs self Management
Authors: Nicula D , Ghimiși S S
Published: June 2019

It’s estimated that in 2017 there were 111 billion lines of new software code generated by developers and most lines were written within a team. Producing software is a creative activity and therefore very different from mass-production lines, because each algorithm tries to solve a different problem. For many years, traditional system development life cycle has been used as the main algorithm for how programmer teams should work to deliver software products. Waterfall methodology is successfully used in simple, unchanging projects but its main drawback is how it handles change. Scrum encourages the creativity of each member of the team, allowing all of them to take on the role they want during the project. Each person can be a developer, a tester, a designer, depending on the responsibilities he takes between two sprints. Considering the diversity of IT projects, it makes sense to understand in what kind of projects we should use the Scrum methodology and where there is a need for more explicit management and control.
Some aspects regarding negotiation in business
Authors: Săvescu D
Published: June 2019

Paper presents some aspects regarding negotiation process used in technological transfer, negotiations strategies, partners orientation in negotiation time, WIN-WIN, or WIN-LOOSE, or LOOSE-LOOSE position, tactics and technics used in negotiation.
Virtual instrument for technical and economic standpoint evaluation of dimensional measurement methods and devices for the machined components finished products
Authors: Braun B C
Published: June 2019

The paper presents a research stage, within PhD Thesis, focused on critical analysis of the solutions for quality insurance in the production activity, standpoint dimensional inspection. The key was the programming of a flexible and efficient software environment, which will help the operator to make the proper decision on the best method and optimal means of dimensional measurement of various categories of fabricated components. It is practical one and it could be very important for productivity increasing, for low costs and also for finite products high quality. To accomplish this software application it were defined as inputs several criteria, like: inspection process timing, measuring precision, devices costs, process costs and energetic consumption. The most part of these criteria (process duration, measuring precision, devices costs) was possible to be established very properly, due to some previous analytical and empiric results, associated to several tested measuring devices
Model identification of dengue fever spreading using firefly algorithm and backpropagation neural network
Authors: Fitania S A , Damayanti A , Pratiwi A B
Published: June 2019

Dengue Fever is one of Indonesia’s well-known medical problems where the range spread territories have became more extensive alongside with mobility and population growth. Considering that a large number of population in East Java - Indonesia has been infected, the identification of Dengue Fever is needed in order to anticipate and minimalize the terrible possibilities that could happen. The aim of this research is to obtain the result of Dengue Fever spreading model identification using Firefly Algorithm and Back-propagation Neural Network. Back-propagation Neural Network identification is proposed to estimate the spreading of Dengue Fever based on actual data. The process begins with estimating the parameters using Firefly Algorithm then identifying the model using Back-propagation Neural Network. Based on the implementation and simulation on the Dengue Fever spreading data in East Java-Indonesia from January 2013 to December 2017, model was succesfully identified where the error value between estimated data and actual data was 0.0242.
Synthesis of Carbonated Hydroxyapatite Derived from Snail Shells (Pilla ampulacea): Effect of Carbonate Precursor to the Crystallographic Properties
Authors: Komang Januariyasa I , Yusuf Yusril
Published: June 2019

This study aimed to investigate the effect of the amount of carbonate in synthesis to the crystallography properties of carbonated-hydroxyapatite (CHAp) using the snail shells as the calcium source. Snail shells were cleaned, milled, and sintered at 1000°C for 4 hours to get CaO powder. CHAp synthesized by co-precipitation method. The molar ratio CO3
2-/PO4
3- was varied 0/6, 2/6, 3/6, and 6/6. Meanwhile, the molar ratio of Ca/P was kept at 1.67. After synthesis, the solution was aged, centrifugally washed, dried, and sintered at 400°C for 2 h in the air atmosphere. A scanning electron microscope (SEM) was used to observe the morphology of CHAp. An energy dispersive spectroscopy (EDS) was used to determine the chemical composition of CHAp. An X-Ray Diffractometer (XRD) was conducted to analyze the crystallography of CHAp. Fourier transform infrared (FT-IR) was used to evaluate the chemical structure of the CHAp. The XRD spectra of CHAp of all variations show they have apatite phase. There is no secondary phase observed in XRD spectra. The results of FTIR and EDS supported the XRD results. The increasing of carbonate amount in synthesis decreased the crystallinity and crystallite size of CHAp. The lattice parameter a-axis was decreased, but the lattice parameter c-axis was increased as the amount of carbonate increased in the synthesis process. The increasing of carbonate amount in synthesis decreases the crystallite size of CHAp. The results demonstrate that the amount of carbonate in synthesis affects the crystallography properties of CHAp.
Effect of Silver Substitution on Electrical Transport and Magnetoresistance of La0.8Ca0.2MnO3
Authors: Munazat Dicky Rezky , Kurniawan Budhy , Imaddudin Agung , Kamila Rina , Razaq Dhawud Sabilur
Published: June 2019

In this work, we have investigated the effect of silver substitution on electrical transport behavior and magnetoresistance of La0.8-
xAgxCa0.2MnO3 (x = 0 and 0.05). Preparation and study of structural and microstructure of both samples have been reported on previous work. Temperature-dependent resistivity has been measured at temperature range of 15-285 K with zero field cooling. Magnetoresistance effect has been measured at 15, 100, and 285 K with magnetic field up to 1 T. The electrical transport behavior of both samples are quite well described by a theory based on the Percolation model. The electrical conduction mechanism at low temperature can be explained by a theory based on Kondo-like spin-dependent scattering, electron-electron, electron–magnon, and electron-phonon scattering. It was found that silver substitution increases the metal-insulator transition temperature (TM-I) from 197.55 to 277.56 K, and Curie temperature (Tc
Mod) from 217.25 to 278.65 K. Moreover, the maximum magnetoresistance value of both samples was obtained at 15 K.
Electrodeposition of Platinum (Pt) Particles as a Catalyst of Hydrogenation of Acetone
Authors: Rahayu Yusnita , Budi Setia , Fauzia Vivi
Published: June 2019

Heterogeneous catalysts play an important role in accelerating chemical reactions in order to save energy and cost during the reaction process. Platinum (Pt) has received a great deal of attention for its application in many catalytic processes, but very few studies have evaluated it in the hydrogenation process of acetone. In this study, Pt particles were successfully grown on an indium tin oxide (ITO) coated glass substrate by means of a facile, one-step, and template-free electrodeposition method using a solution containing 2.0 mM H2PtCl6and 0.5 M H2SO4at room temperature. Potentiostatic and galvanostatic methods were employed to conduct the electrodeposition process under different potentials, current densities, and deposition times to observe their influence on the morphology of the electrodeposited Pt particles. It was found that the morphology of the particles could be facilely manipulated by adjusting the deposition current and potential by using the galvanostatic and potentiostatic methods, respectively. The potentiostatic method produced a spherical or bayberry-like shape whereas the galvanostatic method produced a flower-like shape. The sharp tips on the surface of the bayberry-like shape are electron-rich sites that can break the C = O bond in acetone, thereby forming C-OH bonds that can generate isopropanol molecules.
Synthesis of Organonitrogen Compounds from Eugenol through The Ritter Reaction and The Toxicity Test on Artemia salina Leach.
Authors: Rahman Mohammad Farid , Pratama Ardhya Ayu
Published: June 2019

Eugenol or 4-allyl-2-methoxyphenol is the main component in clove oil which can be used as a starting material in organic synthesis. One of the example is synthesis of organonitrogen compound through the Ritter reaction. Eugenol as a carbocation precursor is reacted with acetonitrile, in the presence of a strong acid catalyst H2SO4, to form organonitrogen compounds. The number of moles in the reaction of eugenol:acetonitrile:H2SO4 is 0.1:0.5:0.1 moles. The reaction was carried out at several conditions namely at ice temperature (0°C) for 4-hours reaction time, at room temperature (27°C) for 4 hours reaction time, and at reflux temperature (90°C) for 4, 8 and 16 hours reaction times. The products were characterized using UV-Vis, IR, and GC-MS. The 4-hours (0°C) and 4-hours (27°C) reactions did not produce any organonitrogen compounds. Meanwhile the 4-hours (90°C) reaction produces organonitrogen compounds, eugenyl acetamide. The 8 - and 16-hours reflux temperature (90°C) reactions are also gives organonitrogen compounds, namely eugenyl acetamide (8% yield in 8-hours reaction time and 13% yield in 16-hours reaction time) and isoquinoline (7% yield in 8-hours reaction time and 11% yield in 16-hours reaction time), in which the yield was increased as the reaction time increased. The toxicity level of the crude obtained from the 16-hours reflux temperature (90°C) reaction time was tested using the Brain Shrimp Lethality Test method to Artemia salina. The result shows that LC50 value is 16 ppm (higher than that of eugenol) and is classified as having a strong toxicity activity.
Optimisation of Methyl Orange Photodegradation Using TiO2-Zeolite Photocatalyst and H2O2 in Acid Condition
Authors: Aziztyana Aprilya Putri , Wardhani Sri , Prananto Yuniar Ponco , Purwonugroho Danar , Darjito
Published: June 2019

This paper discusses an optimisation of methyl orange photodegradation using TiO2-zeolite photocatalyst and H2O2 (with condition of pH 2, 10 ppm, UV light). A 15 mmol TiO2 in 1 gram activated zeolite was used. The influence of H2O2 concentration (4, 8, 12, 16%) and irradiation time (20, 30 40, 50, 60 minutes) was also investigated, as well as initial methyl orange concentration (10, 20, 30 ppm) toward reaction rate constant. As the H2O2 concentration increase, the photodegradation percentage is also increased until it reaches optimum condition (H2O212% for 10 ppm MO solution). Identical effect also showed by the irradiation time in which an optimum point reached at 60 minutes (for 10 ppm MO solution) and 50 minutes (for 20 and 30 ppm MO solutions). Moreover, the higher initial MO concentration used, the lower reaction rate constant obtained. The highest rate constant was shown by MO solution of 10 ppm. The reuse of TiO2-Zeolite photocatalyst remains effective and efficient in photodegradation of methyl orange in solution for up to 4 times.
Quantitative risk modelling of occupational safety in green-port
Authors: Andriani Debrina Puspita , Novianti Vina Dwi , Adnandy Rheza , A’yunin Qurrota
Published: June 2019

Three industrial revolutions are known to have been able to improve the welfare of the community. The fourth industrial revolution or industry 4.0 made many studies carried out on plans, implementations, and other actions that will affect the community. Some industries also began competing to apply industry 4.0 in their systems, including case in this study. This study was conducted in one of the port terminals that are known to be the one and only port that has implemented semi-automatic technology and environmentally friendly in the developing countries. The port operates semi-automatically, so the operating system uses computerization and minimal manpower. As a modern port, this port is equipped with advanced technology, such as automated stacking cranes, ship to shore, and grab ship un-loader, CNG trucks, combined terminal tractors, and others. Port working system is also different from the other ports where only equipment and vehicles that fuelled electricity and gas are allowed to operate in this port, so they also are known as green-ports. Based on preliminary research that had been done, even though the technology and work systems that are applied are sophisticated, but it was known that there were still some occupational accidents that should not have happened, especially in the ship to shore area. The aim of this research was conducted to identify the probability of hazards that occur based on historical data and minimize the risk of further occupational accidents using risk analysis and modelling. Statistical, mathematical, and computational approaches were carried out to obtain risk quantification and develop risk mitigation and response strategies. Thus, the results of the study are expected to help this port as a pilot green-port for other ports, so that it will have a massive positive impact on the change in a more environmentally friendly transportation system.
Kernel Spherical K-Means and Support Vector Machine for Acute Sinusitis Classification
Authors: Arfiani  , Rustam Zuherman , Pandelaki Jacub , Siahaan Arga
Published: June 2019

Acute sinusitis is an inflammation of the sinus which causes the cavity around the sinus to swells due to accumulated mucus. It makes the patient experience difficulty in breathing through the nose. Generally, it is caused by the common cold, and in most cases, the patient recovers within seven to ten days. However, persistent acute sinusitis can cause severe infections and other complications. Therefore, it requires timely detection and more accurate method of classification. Many techniques have been used to classify acute sinusitis but, in this study, the machine learning methods which includes Kernel Spherical K-Means (KSPKM) and Support Vector Machine (SVM) was applied. SPKM is the application of K-Means, in this research, it was modified by changing the inner product with kernel function to ensure linear data separation on higher dimensions for the maximization of SPKM performance. The SVM is a binary classification method that helps to create a model with good generalization ability. We used CT scan result data from RSCM, Central Jakarta. Simulations were performed with different percentage of training data. The results were compared in terms of Accuracy and Running Time. The score showed that the performance of KSPKM attained an accuracy rate of 97%, while SVM reached 90%.
Continuous Ranked Probability Score Validation Methods in Mixture Bayesian Model for Microarray Data in Indonesia
Authors: Astuti Ani Budi
Published: June 2019

Validation in statistical modeling becomes a very important part to get information on how well the model has been built. Algorithm of Continuous Ranked Probability Score (CRPS) is a validation method of goodness of fit model in statistical modeling. A model that has a small CRPS value and has a small statistical significance, then the model is declared fit for data. Conversely, if a model has a large CRPS value, then the model is declared not fit for data. Several applications of the CRPS Algorithm have been developed for unimodal distribution models. Bayesian mixture is a modeling with Bayesian approach where data has a multimodal distribution. Characteristics of multimodal distribution are owned by microarray data in Indonesia, namely data on gene expression differences for several gene IDs from Chickpea plants in Indonesia. The purpose of this study was to obtain a performance from the Continuous Ranked Probability Score (CRPS) Algorithm as a goodness of fit model method in Bayesian Mixture Model (BMM) modeling for microarray data in Indonesia in a series of activities to find new varieties of Chiekpea plants that are resistant to attack by pathogenic fungal diseases Ascochyta Rabiei. The results of this study have succeeded in establishing the Algorithm of Continuous Ranked Probability Score (CRPS) for the distribution of normal mixture for data on gene expression differences of Chickpea plants in Indonesia as a result of microarray experiments with Bayesian approaches. BMM modeling on microarray data is declared fit because it has a small average value of CRPS, which is 0.0412 to 0.385.
Comparison of Cubic SVM with Gaussian SVM: Classification of Infarction for detecting Ischemic Stroke
Authors: Bagasta Amanda Rizki , Rustam Zuherman , Pandelaki Jacub , Nugroho Widyo Ari
Published: June 2019

Ischemic Stroke is a condition whereby the blood supply to the brain is disrupted or reduced due to a blockage and if it is not treated immediately will cause the death of the brain. A decrease in blood flow resulting in dead brain tissue can be called an infarction. The classifications of infarction help the health sector in detecting ischemic stroke in patients. In medicine, CT scans can be used to identify Infarctions and for detecting Ischemic Stroke in patients. Therefore, studying the CT scans is crucial in helping doctors obtain functional information about the surrounding brain tissues which will be used for detecting infarction in the brain. Since it is important to pay more attention at the time of choosing the best method that gives the best results, therefore this study proposes to compare between two types of methods, Gaussian Support Vector Machine (Gaussian SVM) and Cubic Support Vector Machine (Cubic SVM). The Cubic SVM could be an efficient method for infarction classification with accurate performances as high as 80%.
Estimation of Truncated Spline Function in Non-parametric Path Analysis Based on Weighted Least Square (WLS)
Authors: Hidayat Muhamad Fariq , Adji Achmad Rinaldo F. , Solimun
Published: June 2019

The purpose of this research is to identify a particular relationship pattern among predictors and response variables where the response variables are multi-response and correlated. Path analysis is one of the appropriate statistical parametric method to estimate the parameter when the curves are known, but in fact the curves is unknown. Nonparametric approach is a suitable method to estimate the unknown curve in Path Analysis. Truncated spline provides a powerful tool for estimating curve in non-parametric path model with the optimal knots will be estimated by using Generalized Cross Validation. Truncated spline estimator is obtained from Weighted Least Square (WLS) technique that depends on polynomial degree and knot.
Spline Truncated Estimator in Multiresponse Semiparametric Regression Model for Computer based National Exam in West Nusa Tenggara
Authors: Hidayati Lilik , Chamidah Nur , Nyoman Budiantara I
Published: June 2019

Multiresponse semiparametric regression model is a combination of parametric regression model and nonparametric regression model with response variables more than one and correlate. The estimate used in estimate the parameters is spline truncated. Excess spline truncated is a model that has excellent statistical and visual interpretation and can model data with changing patterns on certain sub-intervals, because spline is a kind of polynomial pieces. The data used in this study is the value of Computer Based National Examination (CBNE) Vocational High School (VHS) in the province of West Nusa Tenggara (NTB) in 2017, each subject tested on CBNE serve as response variables. Based on the significant correlation test results obtained p-value <0.05 so it can be concluded that there is correlation between the responses. The result of the multiresponse semiparametric regression model estimation is obtained by the best model with the value of MSE of 49,608; R2 of 0.84 and minimum GCV value of 0.00000323 so it can be concluded that the value of CBNE VHS in NTB province satisfies goodness of fit criterions.
Consumer Satisfaction on Mocaf (Modified Cassava Flour) Based Food Products in Supporting Industrial Revolution 4.0: SEM Approach
Authors: Isaskar Riyanti , Darwanto Dwidjono Hadi , Waluyati Lestari Rahayu , Irham
Published: June 2019

The increase in the snack food industry in Indonesia is one of the effects of improving the current lifestyle. Along with the progress of the digitalization era, technology and marketing strategies that take advantage of the industrial revolution 4.0 demand for snacks is also felt to grow rapidly. Likewise with the growth of culinary tourism provides an opportunity for small industries in the food sector to innovate in developing their products to be attractive to tourists. Mocaf (modified cassava flour) is local flour produced from cassava through a fermentation process, in the long-term it can be used as a substitute for wheat flour. This study aims to determine the variables that affect consumer satisfaction with mocaf-based food products. Purposive sampling technique was applied as a method for determining the sample, with a sample size of 145 people. The analytical method used is structural equation model with the help of warp-PLS software using two exogenous variables namely product quality variable (X1) and price variable (X2) also satisfaction endogenous variable (Y). The results of the analysis show that product quality variables have no significant effect on customer satisfaction, while the price variable has a significant positive effect on customer satisfaction. This shows that in the consumption of mocaf-based processed products, consumers consider product prices more than product quality to influence satisfaction.
Alternative Analytic and Friendly Solution of the Bose-Einstein Integral
Authors: Juwono Alamsyah M. , Istiroyah  , Nuriyah L.
Published: June 2019

A study to find an analytic, and fairly friendly, solution of Bose-Einstein Integral has been conducted, by employing various common mathematical relations, mainly the Fourier Series. The result obtained was without approximation, and did not involve any divergent series. This study was carried out with motivation to obtain analytic solutions from Integral Bose-Einstein, which is very important in the study of Planck Distribution of blackbody radiation, and in Bose-Einstein statistic; and to show that the Bose-Einstein Integral can, in fact, be solved without involving complicated special functions. The Bose-Einstein Integral, surely, had been solved by large number of authors, generally, by utilizing various special functions, such as, by using the Riemann-Zeta function [1][2][6][7]. This study produced the same results as previously obtained through various ways, that is π
4 / 15, which guarantees that the steps we conducted were correct mathematically.
Admission Test Modelling of State Islamic College in Indonesia Using Local Linear for Bivariate Longitudinal Data
Authors: Nidhomuddin  , Chamidah N , Kurniawan A
Published: June 2019

The main challenge in the development of education is improving the quality of education and equitable education. Improving the quality of education is needed in order to create high-quality human resources. Equitable education carried out also still has problems with the uneven quality of education in each region. The aim of this research is to determine the effect of public senior high school status on the admission test scores, i.e., scholastic aptitude test score and Islamic test score of state Islamic colleges in Indonesia. In this research we use a local linear estimator to estimate nonparametric regression model for longitudinal data, and then apply it to the data of admission test scores of state islamic colleges in Indonesia based on the percentage of public senior high school. The result shows that the pattern of the scholastic aptitude test and Islamic test based on the percentage of public senior high school of state Islamic colleges in western Indonesia is different from that in eastern Indonesia. The result of this research can be used by the government to make policies so that the quality of state Islamic colleges will be better by increassing the admission test scores.
Estimation Parameter of Generalized Poisson Regression Model Using Generalized Method of Moments and Its Application
Authors: Girik Allo Caecilia Bintang , Otok Bambang Widjanarko , Purhadi
Published: June 2019

Poisson Regression is a standard model for data counts that can be used to determine the relationship between the response variable and predictors variables. Equidispersion is assumptions that must be met in Poisson Regression. Equidispersion is a condition that the variance of the response variable is equal with the average of the response variable. In real cases, these assumptions are often not meet. In real cases, there are overdispersion and underdispersion cases. Generalized Poisson Regression (GPR) is one method that can handle cases of overdispersion and underdispersion. The GPR model is used to estimate regression parameters. Many articles proposed to use only Maximum Likelihood Estimation (MLE) to estimate the parameters of GPR. This article will develop the parameter estimation method of the GPR model, which is using the Generalized Method of Moments (GMM). GPR model is applied in the case of diarrhea in infants in Pasuruan Regency, East Java. The best model is chosen by the value of AICc. The smaller the value of AICc, the better the model. The best model is a model that includes exclusive breastfeeding, complete basic immunization, and healthy living behavior in the model.
Network Analysis of The Brazil Nut Effect Phenomenon with a Single Intruder
Authors: Rahmadhan Putra Muhammad Iqbal , Rudiawan Aufa , Andariwulan Wahyuni , Berasategui Rubén García , Viridi Sparisoma
Published: June 2019

One phenomenon that can be observed in granular systems is the Brazil Nut Effect (BNE), that is, a phenomenon in which large-size particles lift up when vibrated vertically. In this experiment, structural changes in a pseudo-two-dimensional model of a granular system experiencing BNE were observed from the perspective of network analysis. The system consisted of 199 granular beds of 0.68 cm of diameter with a 2.5 cm diameter intruder placed in a 3mm wide double-window box that was slightly larger than the thickness of the bed and the intruder. The system was subjected to vibrations with a frequency of 13.33 Hz and an amplitude of 0.75 cm, so the BNE could be observed. For the purpose of the analysis, the granular beds were considered the nodes of a network and the relationships between adjacent beds (were contact force occurred) represented its edges. The analysis, consisting of image processing, network extraction, network parameters calculation and community detection, was performed using Wolfram Mathematica v. 11.3. The experiment was able to calculate the change in the network parameters including degrees, clustering coefficients, betweenness centrality, and modularity for the system with intruders and systems without intruders. The parameter values corresponding to each system were markedly different, clearly showing the influence of the intruder. The authors were also able to successfully map the evolution of the community structure in both types of granular systems one step at a time using a modularity optimization method.
Kernel Based Fuzzy C-Means Clustering for Chronic Sinusitis Classification
Authors: Putri Rezki Aulia , Rustam Zuherman , Pandelaki Jacub
Published: June 2019

Sinusitis is an inflammation of the sinus wall, a small cavity interconnected through the airways in the skull bones. It is located on the back of the forehead, inside the cheek bone structure, on both sides of the nose, and behind the eyes. Chronic sinusitis is caused by infection, growth of nasal polyps, or irregularities of the nasal septum. This condition can affect teenagers, adults, and even children. To classify sinusitis we use Kernel Based Fuzzy C-Means (FCM) Clustering Algorithm, which is the development of Fuzzy C-Means (FCM) Algorithm. FCM is one of the widely used clustering technique. FCM algorithm comprises of sample points used to make whole and sub vector spaces according to the size of the distance. However, when non-linear data is separated, the convergence is inaccurate and slow. To overcome this problem, a Kernel-Based Fuzzy C-Means algorithm that makes use of kernel functions as a substitute for Euclidean distance utilized. It maps out samples to high-dimensional space to increase the differences between cluster centres, so they can overcome FCM deficiencies and improve linear machine capabilities. Data was obtained from the laboratory of Radiology at Cipto Mangunkusumo National General Hospital, Indonesia, with a 100% accuracy.
Lung Tumor Classification on Human Chest X-Ray Using Statistical Modelling Approach
Authors: Rizka N. , Chamidah N.
Published: June 2019

Lung tumor is a group of abnormal cells that are formed from the process of excessive and uncoordinated cell division in the lung or known as a neoplasia. Neoplasia refers to the growth of new cells that are different from the growth of cells around it. The Tumor can formed to be benign tumors that not cause cancer and malignant tumors that can cause cancer. Chest X-ray is the most technique that used for detecting a lung tumor. Image processing is done by mean for distinguishing the classification lung tumor. Based on previous research the most used method is the mathematical method, but the result obtained are not maximal. Therefore, in this study we propose methods to classify lung tumor by using statistical modelling approach with logit link function based on parametric model, and nonparametric model using penalized spline estimator. Based on the proposed method, we get the classification accuracy of 80% for parametric model approach and 85% for nonparametric model approach, it means that the nonparametric model approach is better than the parametric model approach.
Naïve Bayes Classifier Models for Predicting the Colon Cancer
Authors: Salmi Nafizatus , Rustam Zuherman
Published: June 2019

Cancer has been known as a disease consisting of several different types. Cancer is a life threatening disease in the world today. There are so many types of cancer in the world, one of which is colon cancer. Colon cancer is one of the number one killers in the world. However, because there isn’t any obvious symptom of colon cancer at an early stage, people do not realize that they suffer from it. Even though cancer formation is different for each type of cancer, it is still a big challenge to make cancer classification with good accuracy. Many machine learning has been applied to the data of human’s genes in order to get the most relevant genes in the classification of cancer. The author proposes the Naïve Bayes Classifier model as a classification method to show that the model has good accuracy, good precision, good recall, good f
1 — score in classifying the data of patients suffering from colon cancer or not. In this proposed model, Naïve Bayes Classifier is a technique prediction based on simple probabilistic and on the application of the Bayes theorem (or Bayes rule) with a strong independence assumption. Therefore, this model is able to make higher classification accuracy with less complexity. In particular, it achieves up to 95.24% classification accuracy, thus this model can be an efficient analysis tool.
Forecasting the Amount of Pneumonia Patients in Jakarta with Weighted High Order Fuzzy Time Series
Authors: Tricahya Sebastian , Rustam Zuherman
Published: June 2019

Forecasting the amount of Pneumonia patients could help medical practitioners to prepare the required medicines, aid-workers, or even prevent it by sharing knowledge to parents, elders, and smokers. This problem poses great concerns on the lives of many people, therefore, adequate accuracy is required in forecasting. Fuzzy Time Series (FTS) is an alternative way to forecast data. By using ARIMA and Holt’s Exponential Smoothing, there are some problems that are difficult to obtain the best model. Using our FTS method, we modified the Cheng algorithm by using higher order (using two or more historical data) to make the accuracy better by seeing the Mean Absolute Percentage Error (MAPE). Data was selected from the amount of Pneumonia Patients in Jakarta from 2008 to 2018. We use R to carryout ARIMA and Holt’s Exponential Smoothing. Forecasting’s accuracy will decrease if the timeframe between these occurrences is lengthy. As a result of this, we made use of 5 periods which are January until May 2019. The result obtained was compared against ARIMA and Holt’s Exponential Smoothing, as well as the MAPE are 9.70%, 16.85%, and 18.55% respectively.