bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthesized vanadium doped ZnO through the co-precipitation method
Authors: Djaja N F , Taufik A , Saleh R 
Published: January 2020

Abstract
In this study, vanadium modified ZnO nanoparticles were synthesized using the co-precipitation method. The amount of vanadium content was varied from 5, 8, and 16 atomic percentages (at.%). The structural properties of the prepared samples were characterized using X-ray diffraction (XRD). The results show that all the prepared samples had a hexagonal wurtzite structure from ZnO nanoparticles. The grain size and lattice strain were calculated using Williamson-Hall plots with a uniform deformation model approach. The elemental analysis characterized using energy dispersive X-ray measurement indicated that the total vanadium concentrations of the samples were about 5, 8, and 16 at.%. In addition, the UV-Vis reflectance analyses show that the reflectance spectra of vanadium doped ZnO decreased in visible light region with increased vanadium content.
Modeling total crime and the affecting factors in Central Java using geographically weighted regression
Authors: Runadi T , Widyaningsih Y , Lestari D 
Published: January 2020

Abstract
Analysing the relationship between number of crime cases and affecting factors became an interesting research topic over the last ten years. The total number of crime in Indonesia did not show a consistent decrease. In order to upgrade people safeness quality, the government need to know the factors influence people committing crime acts. Rather than using classical regression analysis, geographically weighted regression (GWR) was preferable since it gave a better representative model by effectively resolve spatial non-stationary problem which is generally exist in spatial data of social phenomenon. Spatial non-stationary is a situation when the relationship between variables are significantly different in each location of observation point, so that classic regression analysis will result a misleading interpretation in some location. GWR handled the spatial non-stationary problem by generating a single model in each observation point which allow different relationship to exist at different point in space. This study used number of crime cases (y) as the dependent variable and the factors which affect the number of crime cases as independent variables that consist of the number of illiterates (X1), the number of unemployed (X2), the number of poor population (X3), population density (X4), the number of victims of drug (X5). This study used secondary data collected by POLRI, BPS and Indonesian Ministry of Social Affairs in Central Java during 2015. GWR generated model for 35 city/regency in Central Java.
Comparison of Support Vector Machine Recursive Feature Elimination and Kernel Function as feature selection using Support Vector Machine for lung cancer classification
Authors: Rustam Z , Kharis S A A 
Published: January 2020

Abstract
Cancer is the uncontrolled growth of abnormal cell that need a proper treatment. Cancer is second leading cause of death according to the World Health Organization in 2018. There are more than 120 types of cancer, one of them is lung cancer. Cancer classification has been able to maximize diagnosis, treatment, and management of cancer. Many studies have examined the classification of cancer using microarrays data. Microarray data consists of thousands of features (genes) but only has dozens or hundreds of samples. This can reduce the accuracy of classification so that the selection of features is needed before the classification process. In this research, the feature selection methods are Support Vector Machine Recursive Feature Elimination (SVM-RFE) and Kernel Function and the classification method is Support Vector Machine (SVM). The results showed SVM using SVM-RFE as feature selection is better than SVM method without using feature selection and Gaussian Kernel Function.
Comparing Poisson-Inverse Gaussian Model and Negative Binomial Model on case study: horseshoe crabs data
Authors: Putri G N , Nurrohmah S , Fithriani I 
Published: January 2020

Abstract
Poisson Regression analysis is commonly used for dependent variable that has non-negative value, called count data. Poisson Regression has an assumption that mean of dependent variable equal to its variance. On over dispersion case where the variance is greater than mean, poisson regression is inconvenient to used because it may underestimate the standard error of regression parameters and consequently giving misleading inference. Poisson-Inverse Gaussian and Negative Binomial regression model can be used on over dispersion data. This paper will discuss about Poisson-Inverse Gaussian regression model, Negative Binomial regression model and comparing them in terms of Goodness-of-fit (GOF) statistics on case study of horseshoe crabs data. According to the result, pseudo R-squared value of P-IG regression model is greater than the Negative Binomial regression model. It shows that P-IG regression model is better than Negative Binomial regression model.
Robust Ridge regression to solve a multicollinearity and outlier
Authors: Jeremia N E , Nurrohmah S , Fithriani I 
Published: January 2020

Abstract
Regression analysis is one of many methods used for analysing data. Method that used for estimating parameter in linear regression model is ordinary least square (OLS). OLS will give best estimator when all the assumptions are met. But in reality, sometimes not all the assumptions are met. Assumptions that usually violated are multicollinearity and outlier. Ridge regression is a regression method that give constrain on the parameters that used to deal with multicollinearity, meanwhile Robust regression is used to overcome the presence of outlier. Robust regression is a regression method that has robust property that achieved by using S-estimation is used. Ridge regression and Robust regression combined into Robust Ridge regression to overcome multicollinearity and outlier simultaneously.
Determination of net premium rates on Bonus-Malus system based on frequency and severity distribution
Authors: Pratama A S , Nurrohmah S , Novita M 
Published: January 2020

Abstract
Vehicle insurance companies in many countries use the Bonus-Malus System to determine the policyholder’s net premium. The determination of net premiums on the Bonus-Malus System is based solely on the frequency of claims and ignores the severity of claims. This is unfair to policyholders who have small claims. To overcome this problem, the net premium determination method in Bonus-Malus System was developed taking into account both the frequency and severity of claims. Frequency and severity be assumed to be independent. In determining the net premium, a posterior distribution of parameters of the frequency and severity distribution is required. In the case of frequency and severity independent, the determination of the posterior distribution for frequency and severity is performed separately. This thesis discusses the determination of net premium based on frequency distribution and severity distribution for frequency and severity independent.
Implementation of K-Means and crossover ant colony optimization algorithm on multiple traveling salesman problem
Authors: Kusumahardhini N , Hertono G F , Handari B D 
Published: January 2020

Abstract
Multiple Traveling Salesman Problem (MTSP) is a generalization of the Traveling Salesman Problem (TSP). MTSP is an optimization problem to find the minimum total distance of m salesmen tours to visit several cities in which each city is only visited exactly by one salesman, starting from origin city called depot and return to depot after the tour is completed. In this paper, K-Means and Crossover Ant Colony Optimization (ACO) are used to solve MTSP. The implementation is observed on three datasets from TSPLIB with 2, 3, 4, and 8 salesmen. Analysis of results using K-Means and Crossover ACO will be compared. The effect of selecting a city as depot on the total travel distance of tour will also be analyzed.
Hermite-Hadamard-Fejèr type inequalities for s-convex functions in the second sense via Riemann-Liouville fractional integral
Authors: Hakiki M T , Wibowo A 
Published: January 2020

Abstract
The convex function is one of the topics in mathematics that is closely related to the theory of inequality. Furthermore, the definition of convex function has an extension, which is the first and second kind of s-convex function, for fixed s ∈ (0,1. Convex function has a relation to the Hermite-Hadamard-Fejèr inequality, which is an integral inequality involving a convex function. Further development of these inequalities involves the s-convex function and through the concept of fractional integral. In this study, we discuss the Hermite-Hadamard-Fejèr type inequality that applies to the second kind of s-convex function via the Riemann-Liouville fractional integral. From these results, the relationship between these inequalities with the same type of inequality for convex function, are obtained.
Preference analysis of determining jobs using conjoint analysis
Authors: Karima R D , Setiadi R , Siswantining T 
Published: January 2020

AbstractNowadays, there are many graduates who are not directly employed after receiving bachelor’s degree. The graduates who are not employed seem largely unaware of career opportunities and unsure of how to apply their skills in the workforce. This indicates a lack of career guidance, coaching and counselling. This research aims to study people’s preferences on determining their jobs by using conjoint analysis. Four factors are evaluated: (1) income, (2) suitability of the workplace with educational background, (3) field of works, and (4) working hours, which has different level category values. Monotonic analysis of variance is used to analyze the data and the results are (1) utility value which is useful to know the most desirable level of each attribute and (2) its relative importance value to know the most considered attribute on determining their jobs. The full profile method of conjoint analysis shows that income is the most considered attribute value.
Estimating parameter in two-way analysis of variance when variance between cells is heterogeneous
Authors: Marantika A , Fithriani I , Nurrohmah S 
Published: January 2020

Abstract
Analysis of Variance (ANOVA) is a technique in statistics to test the mean differences of more than two groups in the presence of factors that may affect the mean difference. There are three types of analysis of variance, namely one-way analysis of variance, two-way analysis of variance, and multi-way analysis of variance. In this paper, we will discuss two-way analysis of variance which can be seen also the interaction of two factors. In the two-way analysis of variance, there are assumption that must be met, is observed in the cell or group must be normally distributed, the observations between cells or groups are mutually independent, and the variance between cells or groups is homogeneous. A common problem with two-way analysis of variance is unfulfilled assumptions, one of which variance between cells or groups is heterogeneous. Before determining test statistics for two-way analysis of variance, there are parameters to be estimated. This paper discusses the estimation of parameters for testing the effects of main factors and interaction factors on a two-way analysis of variance when the variance between cells or groups is heterogeneous.
Influence of inducers, Tween 80, and agitation on the enhancing decolorization of black liquor by Trametes versicolor F200
Authors: Zahra Z , Hanifah U , Anggraini R I F , Sari A A , Saefumillah A 
Published: January 2020

Abstract
Black liquor wastewater was generated from bioethanol pre-treatment process. The combination of coagulant-flocculants, Poly Aluminium Chloride (PAC) and Anionic Polyacrylamides 3 % has able to reduce COD concentration 99.8 %. After coagulation-flocculation process, this wastewater was treated by Trametes versicolor F200. The aim of this study was to determine the decolourisation of coagulated black liquor by T. versicolor F200 and the effects of inducers, Tween 80, and agitation to enhance the decolourisation of coagulated black liquor. In addition to the decolourisation rate, COD concentration and enzyme activity were also measured in this study. Further, the characterization of lignin from black liquor was measured by LC-MS to determine the molecular weight of lignin before and after treatment by T. versicolor F200. The result showed that the optimum condition for obtaining the highest decolorization of coagulated black liquor were 97.56 % with addition of 2mM CuSO4, 2mM MnSO4, 2 % Tween 80 and agitation 150 rpm. The ranges of decolourisation during that condition were (97.56 – 97.89) %. Further, the decreasing molecular weight (m/z) of lignin during degradation process (539 to 325) showed that lignin compound can be degraded into smaller compound by using T. versicolor F200.
Characterization of nanoemulsion gotukola, mangosteen rind, cucumber and tomato extract for cosmetic raw material
Authors: Septiyanti M , Meliana Y 
Published: January 2020

Abstract
Agingis related to defacement caused by free radical and the most common signs are fine lines and wrinkles. Wrinkles occur in skin layer called dermis-contained collagen that is responsible in preventing wrinkles. This physiological change on skin made an individual look old, and this is a troubling issue especially for women. Natural substances have an excellent anti-aging remedy to improve skin defection caused by free radical and maintain skin rejuvenation. Itis already proved that gotukola, mangosteen rind, cucumber and tomato extract has antioxidant activity. In this study, these extracts were formulated in nanoemulsion which was prepared in anti-aging topical preparation. This nanoemulsion system was expected to accelerate active agent absorption into skin tissue. It was also investigated the the emulsion stability system by pH, refractive index, viscosity and particle size parameter. It was shown that the anti-aging topical preparation with a composition of 2% Gotukola extract, 2% mangosteen rind extract, 2 % tomato extract and 4% cucumber extract was stable for 2 months of observation with average pH 6.16 ± 0.33; 6.11 ± 0.351, refractive index 1.38817 ± 0.00863; 1.37 ± 0.00453, viscosity 3148 cP ± 1068; 1638 cP ± 1294 and particle size 1.14 μm ± 0.84; 1.64 μm ± 0.99 in 5 °C and ambient temperature respectively. Overall, the emulsion system was relatively stable in both storage temperature 5 °C and ambient temperature. It was also proven to be safe for human application.
The efficiency of hydrogen production by water electrolysis with bitter melon as a media using stainless steel/Fe-Co-Ni electrodes
Authors: Louise I S Y , Aloysius H P , Sulistyani S 
Published: January 2020

Abstract
This study aims to determine the production efficiency of hydrogen gas with the addition of bitter melon using stainless steel/Fe-Co-Ni electrodes on water electrolysis process and also to obtain the smallest required energy of hydrogen gas production. Stainless steel/Fe-Co-Ni was made from electrodeposition stainless steel by using e-DAQ E-Chem instrument at a rate of 50 mV/s for 10 minutes. Electrodeposition result was characterized using linear voltammetry, SEM-EDX (Scanning Electron Microscope-Energy Dispersive X-Ray) and XRD (X-Ray Diffraction). Stainless steel/Fe-Co-Ni electrodes was used as working electrodes on water electrolysis. The process of water electrolysis used 0.5 % NaHCO3 solution and an additional amount of bitter melon (0.1-1 %w/v). Each of the samples was electrolyzed in a cyclic voltammetry by using e-DAQ E-Chem instrument at a rate of 50 mV/s. The study results showed that the addition of bitter melon in electrolyte solution is less efficient to produce the hydrogen gas. But, related to the energy, the smallest required energy of hydrogen gas production by water electrolysis with bitter melon as a media using stainless steel/Fe-Co-Ni electrodes occurs at the addition of 0.6 % (w/v) bitter melon flour, which is 0.001 Volt with the efficiency of hydrogen gas generation was 51.06 %. Thus, we can state that the optimum efficiency of hydrogen gas production occurs at the addition of 0.6 % bitter melon flour in 0.5 % NaHCO3 solution.
Development of a non-enzymatic urea sensor based on a Ni/Au electrode
Authors: Irzalinda A D , Gunlazuardi J , Wibowo R 
Published: January 2020

Abstract
Measurement of urea concentration in urine is a very important parameter for determining the state of kidney health. With this aim, a non-enzymatic urea sensor comprising Ni metal deposited on an Au electrode has been developed. Ni was first deposited on an Au electrode by varying the potential and time, and then the deposited Ni was activated in KOH to generate NiOOH, which can oxidize urea to CO2, N2 and H2 to allow it to be detected electrochemically. The results show that the Ni/Au electrode can be used to detect urea with a limit of detection (LOD) value of 3.35 × 10−2 mM, a sensitivity of 52.20 mMμA−1cm−2 and a linearity of r2 = 0.997 at a deposition potential of −0.45 V vs. Ag/AgCl after a deposition time of 180 seconds. The Ni/Au electrode has good repeatability and reproducibility (%RSD value) of 0.12% (n = 12) and shows good stability with a %RSD value of 1.60% after 9 days. The Ni/Au electrode performance is not disturbed by the presence of any interfering compounds, such as ascorbic acid, glucose, NaCl, and KCl. The Ni/Au electrode can be used to measure urea levels in urine samples, detecting concentrations of as high as 9.615 mM.
Encapsulation of cinnamic acid and galangal extracts in coconut (Cocos nucifera L.) liposomes
Authors: Hudiyanti D , Al-Khafiz M F , Anam K 
Published: January 2020

AbstractCoconut liposomes are used to encapsulate cinnamic acid, red and white galangal extracts. Their encapsulation efficiencies and leakage rates are explored. The encapsulation efficiencies of cinnamic acid, red galangal and white galangal are 62 %, 42 % and 52 % respectively. Addition of 7 % cholesterol increases the encapsulation efficiency of cinnamic acid red galangal and white galangal to 70 %, 50 % and 68 % correspondingly. The red galangal extract has as much leakage rate as the cinnamic acid compare to white galangal extract at all liposomal systems.
Green synthesis of gold nanoparticles supported in Al-pillared bentonite using aqueous leaf extracts of Dracaena angustifolia and their use for reductive degradation of methyl orange
Authors: Melvin M , Bakri R , Yulizar Y 
Published: January 2020

Abstract
We obtained the green synthesis of gold nanoparticles (AuNPs) using suji leaf extract (Dracaena angustifolia) and used the AuNPs to reduce methyl orange. The active substance in suji leaf extract was determined using phytochemical tests to identify components such as terpenoid, steroid, alkaloid, polyphenol, flavonoid, and saponin. The catalyst Al–bentonite@AuNP was prepared by immobilizing HAuCl4 in Al–pillared bentonite, which was then reduced using various concentrations of suji leaf extract [0.1 %–1 % (w/v)]. The AuNPs were characterized using UV–vis spectroscopy and transmission electron microscopy, and the Al–bentonite@AuNP catalyst was characterized using Fourier transform infrared spectroscopy and X-ray diffraction. The application of Al–bentonite@AuNP as catalyst in the reductive degradation of methyl orange yields a degradation percent of up to 34.5 %.
Adsorption of mesoporous carbon modified with triethylenetetramine as a function of carbon dioxide flow time
Authors: Chrisnardy F , Krisnandi Y K 
Published: January 2020

Abstract
We synthesize mesoporous carbon by using the soft-templated method with pluronic F-127 as a structure-directing agent, and phloroglucinol and formaldehyde as carbon precursors. The as-synthesized mesoporous carbon was characterized by using x-ray diffraction, Brunauer, Emmett and Teller (BET), scanning electron microscopy (SEM), energy dispersive x-ray spectroscopy (EDX), and Fourier transform infrared (FTIR) spectroscopy. The as-synthesized mesoporous carbon was activated by using 1M HCl to increase the triethylenetetramine (TETA) as amine group compound loading within mesoporous carbon. Mesoporous carbon and activated mesoporous carbon was modified by using TETA with concentration variations less than 50 wt%. The modified mesoporous carbon was also characterized by using SEM-EDX and FTIR. Adsorption tests were done by using adsorbent mesoporous carbon, activated mesoporous carbon, mesoporous carbon modified by TETA, and activated mesoporous carbon modified by TETA with CO2 gas flow times of 5, l0, 15, 20, 25, and 30 min, a contact time of 15 min, and a flow rate of 20 mL/min. The adsorbed CO2 gas was quantified by using the acid-base titration method. On the basis of the CO2, adsorption test, the acid activation was successfully increased by TETA loading within mesoporous carbon, which increases the ability of the material to adsorb CO2.
Preparation of a TiO2-based dye-sensitized solar cell comprising anthocyanin from mangosteen pericarp (Garcinia mangostana, L.) as the sensitizer: co-pigmentation effect on sensitizer and solar cell efficiency
Authors: Zikri A D , Gunlazuardi J 
Published: January 2020

Abstract
A dye-sensitized solar cell (DSSC) is a device that converts solar energy into electric energy. In this study, TiO2, nanotubes (TiO2-NTs) sensitized with anthocyanin extracted from mangosteen pericarp (Garcinia mangostana L.) were used as part of a working electrode, whereas fluoride-doped tin oxide-platinum (FTO-Pt) was used as counter electrode. TiO2-NTs were grown on a titanium plate via a two-step anodization method. Pt from an H2PtCl6 solution was deposited on an FTO surface prepared by spray pyrolysis. The anthocyanin extract was co-pigmented with benzoic acid to increase the stability of the DSSC and its visible light absorbance. The TiO2 prepared by anodization was characterized by scanning electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, and diffuse reflectance UV-Vis spectroscopy. Photocurrent evaluation using linear sweep voltammetry and multi pulse amperometry indicated that TiO2-NTs were activated by UV light. Sensitization with anthocyanin–benzoic acid increased TiO2-NT’s response to visible light. The anthocyanin extract absorbed light in the visible region (400–600 nm), and as a result of its co-pigmentation with benzoic acid, absorbance increased. The efficiency of various DSSCs was evaluated, and data indicated that with sensitizers like anthocyanin alone or anthocyanin co-pigmented with benzoic acid at different ratios (1:0.5; 1:0.8; and 1:1 (v/w)) efficiency values were 0.2273 %, 0.2297 %, 0.2884 %, and 0.3709 %, respectively. The results indicate that the addition of benzoic acid to anthocyanin can improve DSSC performance.