bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chemical oxygen demand (COD) degradation of herbal, tofu and fertilizer wastewater using UV/Ozone oxidation methods
Authors: Hadiyanto  , Silviana  , PAdetya N , Pratiwi M E , Aripratama A D 
Published: June 2019

Abstract
The herbal, tofu and fertilizer industries contribute considerable waste. Unprocessed waste disposal can cause environmental pollution. The waste contains chemical oxygen demands (COD), and organic substances can be degraded by Advanced Oxidation Processes (AOPs) degradation method. The process of AOPs in this study used a combination of UV rays and ozone to produce hydroxyl radicals. This study was aimed to investigate the effect of UV, Ozone and UV-Ozone methods on COD degradation of herbal waste, tofu, and fertilizer. The result showed that the optimum degradation was obtained at experiment by using UV/ozone method. The COD degradation at tofu wastewater was from 1308 to 942 ppm, herbal wastewater was from 1011 to 414 ppm, and fertilizer wastewater was from 510 to 89 ppm by the use of 4 hours UV-Ozone method.
Routh-hurwitz criterion and bifurcation method for stability analysis of tuberculosis transmission model
Authors: Mahardika R , Widowati  , Sumanto YD 
Published: June 2019

Abstract
Tuberculosis is an infectious disease; it caused by Mycobacterium tuberculosis. In this paper, we discuss how to use the Routh-Hurwitz stability criterion to analyze the stability of disease free of the tuberculosis transmission model. From this method, can be found the number of roots of the characteristic polynomial (eigenvalues) with positive real parts is equal to the number of changes in sign of the first column of the Routh array. If all of the eigenvalues are negative, then the model is stable. While the bifurcation method is used to analyze the stability of the endemic equilibrium point of the tuberculosis transmission, the endemic equilibrium point is locally asymptotically stable if reproduction number greater than one and additional parameters requirement that bifurcation met. Finally, numerical simulations are demonstrated to verify the used method.
Application of the Crystallographic tiling to Increase Competitiveness of the Sand Sediments
Authors: Kartono  , Utomo R H S , Sasongko P S , Udjiani T 
Published: June 2019

Abstract
Mount Merapi eruption in 2010 resulted in the environmental damage and disruption of socio-economic life of the society. Post-eruption cold lava floods carry the volcanic sedimentary materials in the form of sand and stone are very abundant. Unfortunately, the abundance of these natural resources is exploited at low prices. The problem is how to manage the sedimentation to have high economic value. The adaptation efforts to manage this sediment need to be done to immediately restore the social economic slump of society. The sediment management model that can improve economic value and competitiveness needs to be done by maintaining the sustainability of its natural resources. This article contains the results of research on the application of crystallographic tiling to improve the economic value and competitiveness of sand sediments. Three types of sediment-based products are successfully made of tiles, rosters, and paving.
On total edge irregularity strength of dove tail graph with pendant vertices and its subdivision
Authors: Nurdini E , Rosyida I 
Published: June 2019

Abstract
Given a graph G(V, E) with a non-empty set V of vertices and a set E of edges. A total labelling λ: V ∪ E → { 1, 2,. . ., k} is called an edge irregular total labelling if the weight of every edge is distinct. The weight of an edge e, under the total labelling λ, is the sum of label of edge e and all labels of vertices that are incident to e. In other words, wt(xy) = λ(xy) + λ(x) + λ(y). The total edge irregularity strength of G, denoted by tes(G) is the minimum k used to label graph G with the edge irregular total labelling. In this paper, authors investigate the total edge irregularity strength of Dove tail graph with n pendant vertices

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Analysis of mathematical model of HIV-1 infection of CD4+ T cells with CTL response and antiretroviral treatment
Authors: Sutimin  , Sunarsih  , Thahjana Heru 
Published: June 2019

Abstract
A mathematical model is developed to capture the spread of HIV-1 infection within host cells caused by the contact of cell to cell and CTL response. In this paper, we propose a mathematical model of HIV-1 infection in CD4+T cells taking into account viral transmission from cell to cell and CTL response. The HIV transmission from cell to cell is one of the main factor in the spread of HIV infection and CTL response determines viral set point. We analyse the model to investigate the existence and stability of the equilibria. We analyse the local stability of disease free equilibrium by linearization, while the global stability of endemic equilibrium of the system by constructing Lyapunov function. Numerical simulations are presented to find the effectiveness of antiretroviral treatment in different scenarios and to the implication of CTL response in controlling the progression of HIV-1 infection.
Frank copula on value at risk (VaR) of the construction of bivariate portfolio (Case Study: stocks of companies awarded with the IDX top ten blue with stock period of 20 october 2014 to 28 february 2018)
Authors: Handini J A , Maruddani D A I , Safitri D 
Published: June 2019

Abstract
Value at Risk (VaR) is a method to estimate the worst risk of an investment. The stock data is one of the financial time series data which often has high volatility which causes inconstant residual variance. The combination between several stocks in the portfolio makes the assumption of residual normality of the joint distribution model difficult to fulfill. The previous research on VaR by Sofiana in 2011 [3] and Hermansyah in 2017 [4] found that VaR value was reliable only for the data fulfilling normality assumption. Therefore, it is necessary to estimate VaR without ignoring the presence of heteroscedasticity and unfulfilled residual normality of the joint distribution model. This research aims to measure the VaR using Frank Copula-GARCH method with stock return data of BBRI, TLKM and UNVR for the period of 20 October 2014 to 28 February 2018. The research found that a pair of bivariate portfolio was TLKM and UNVR because they had the highest residual correlation value of Rho Spearman of ρ = 0.3204. Based on the data generation obtained using Monte Carlo simulation, the results of the VaR were -0.027883; -0.01886425; -0.01403 with confidence level at 99%, 95%, and 90% respectively.
Modeling of red onion production in Central Java using hybrid ARIMA-ANFIS
Authors: Diarsih I H , Tarno  , Rusgiyono A 
Published: June 2019

Abstract
Red onion is one of the strategic horticulture commodities in Indonesia considering its function as the main ingredients of the basic ingredients of Indonesian food. For increasing production to supply national necessary, Central Java as the main center of red onion production should be able to predict the production of several periods to maintain the balance of national production. The purpose of this research is to get the best model to forecast the production of red onion in Central Java by ARIMA, ANFIS, and hybrid ARIMA-ANFIS method. The smallest RMSE and AIC values measure model accuracy. The results show that the best model for modeling red onion production in Central Java is obtained by hybrid ARIMA - ANFIS model which is a combination between SARIMA ([2], 1, [12]) and residual ARIMA using ANFIS model with input et,1, et,2
on the grid partition technique, gbell membership function, and membership number of 2 that produce RMSE 12033 and AIC 21.6634. While ARIMA model yield RMSE 13301,24 and AIC 21,89807 with violation of assumption. And the ANFIS model produces RMSE 14832 and AIC 22,0777. It shows that ARIMA-ANFIS hybrid method is better than ARIMA and ANFIS.
Comparing Merton model and Gram-Charlier model to capture skewness and kurtosis on bond performance
Authors: Abdurakhman  , Maruddani D A I 
Published: June 2019

Abstract
The existence of skewness and kurtosis in finance data distribution is as a generalization of the normal density. Non-normal skewness and kurtosis of underlying asset of bond issuer significantly contribute to the phenomenon of volatility smile. Merton jump diffusion model is one of the first beyond Black-Scholes model in the sense that it tries to capture the effect of skewness and kurtosis of the asset prices density by a simple addition of a compound Poisson jump process. Another approach to consider the effect of skewness and kurtosis in asset prices for bond valuation is the Gram-Charlier (G-C) expansion. Hermite polynomial is used to get an expansion of the probability distribution in G-C method. In this paper we compare Merton Jump Diffusion (MJD) Model and G-C model in the term of equity and default probability. The result showed that G-C model is more consistent than MJD model when the skewness and kurtosis are taken into account.
Predicting currency crisis in Indonesia based on real output and Indonesia Composite Index (ICI) indicators
Authors: Sugiyanto  , Zukhronah E , Slamet I , Setianingrum M 
Published: June 2019

Abstract
The currency crisis that occurred in the middle of 1997, 1998 and 4th quarter of 2008 was caused by disturbances in the currency system. When there is disturbance in the system then the cause indicators will experience fluctuations and changes in conditions. High fluctuation can be modeled using volatility model, while the changes in condition can be modeled using Markov switching model. Therefore, combination of volatility and Markov switching models is very appropriate to explain the crisis. In this paper, we use real output and ICI indicators on the period of January 1990 until December 2016 to explain the crisis as well as to forecast the possibility of an impending crisis. The results show that the appropriate model is ARCH (1) and Markov switching with 3 states, called SWARCH (3,1) model. This model can catch the crisis that happened in 1998 and 1999 for real output indicator. Meanwhile ICI indicator can explain the crisis in August to December 1997, 1998 and September to December 2008. Based on SWARCH (3,1) model, it can be predicted that Indonesia does not experience currency crisis in one year later.
Gold price modeling in Indonesia using ARFIMA method
Authors: Safitri D , Mustafid  , Ispriyanti D , Sugito  
Published: June 2019

Abstract
Gold investment is the best choice to control finance. Gold is easy to resell if there is a financial need at the unpredictable moment. The data of gold price in Indonesia is a long-term memory data series or a time series data that has a long-term dependency. ARFIMA model is an appropriate model for such long-term memory data series since ARFIMA model has a different parameter value (d) of integer while the value of d in ARFIMA model is non-integer value due to the long-term memory or the long-term dependency. This research aims to obtain the best ARFIMA model of gold price data in Indonesia. It is obtained the value of ARFIMA model (1,d,[3]) with d=1,05716 as the best model.
GARCH-family for measuring price fluctuation risk of harvested dry grain in Pemalang district
Authors: Rahmawati R , Rusgiyono A , Hoyyi A , Maruddani D A I 
Published: June 2019

AbstractValue at Risk (VaR) is a measurement of the value of a risk that estimates the maximum potential loss that may occur in the future within a certain period and a certain level of trust. VaR is widely used in financial data, but has not received the same treatment in agriculture. The risks associated with price fluctuations are one of the most obvious and well-studied aspects of price risk management. In this study, analyze Value at Risk (VaR) based on the GARCH family volatility model for agricultural commodities, especially harvested dry grain at 95% confidence intervals. This study uses the price of harvested unhulled rice at the producer level of Pemalang District from August 2015 to July 2018. Based on the nature of the data, the appropriate model used is the MA (1) – GARCH (1,1) model. The results of this study indicate that the longer the time to invest, the greater the risk it creates.
Valuing risk of changes on corn (zea mays) prices by considering skewness and kurtosis parameters
Authors: Rahmawati R , Tarno  , Maruddani D A I , Hoyyi A 
Published: June 2019

AbstractValue at Risk (VaR) is a measure of risk value by estimating the potential of maximum loss that might occur in future in certain time and a certain level of confidence. The risks faced in agriculture might be in production and marketing of agricultural products. This research aims to estimate the risk value in agricultural commodity – particularly dried shelled corn. Data used was the monthly data of the price of producers in Grobogan in period of November 2015 to July 2018. The data showed the return with the normally undistributed value of skewness and kurtosis. For this, the method of Cornish-Fisher was used in this research to measure the VaR in return that was normally undistributed. At the confidence level of 95%, with the initial capital of 1 million Rupiah, the risk that probably occurred in the following month (1 period) was by Rp 369,173.40 without considering the skewness and kurtosis, and by Rp 22,439.13 by considering skewness and kurtosis. The result of the research showed that, for the return that was normally undistributed, the level of risk obtained from the measurement of VaR by concerning skewness and kurtosis was found more accurate compared to the one without considering the skewness and kurtosis.
Analysis of aquaculture leading commodities in Central Java using Location Quotient and Shift Share methods
Authors: Manullang D , Rusgiyono A , Warsito B 
Published: June 2019

Abstract
The condition of capture fisheries is currently stagnating, even tended to decline, which is indicated by the decrease of production in some fishery development areas in Indonesia. Aquaculture is one solution that can be done. Central Java Province is a province that has a large aquaculture potential, therefore of course Central Java province has leading commodities that become the sector of regional economic development. This research discusses about the potential location for the development of each leading commodities in Central Java Province as a recommendation related to the center of fisheries production. Analytical methods in this research are Location Quotient (LQ) and Shift share. It used to see how big these locations have a potential in the development of aquaculture production and to identify spatial autocorrelation in the amount of aquaculture production using Moran’s index. The analysis of LQ and shift share shows that each district has a different potential in the development of leading commodities production. The value of the Moran’s index obtained equal to -0.1381, that is in the range of -1 < I ≤ 0, indicating that the presence of spatial autocorrelation is negative but small because of near to zero. It can be concluded that there is no similarity of the values between the districts or indicate that amount of aquaculture production among the districts in Central Java is not correlated.
Modeling longitudinal data based on Fourier regression
Authors: Suparti  , Santoso R , Prahutama A , Devi A R , Sudargo  
Published: June 2019

Abstract
Regression analysis is an analysis in statistics for modeling the relationship between predictor variables and response variable. Regression analysis can be performed by two approaches; parametric and non-parametric models. Some commonly used estimators of nonparametric approaches are spline, local polynomial, kernel, wavelet, and Fourier. Fourier nonparametric regression is a regression based on Fourier series with cosine and sinus patterns. Regression analysis can be explored, not only for cross section data but also for longitudinal data. Longitudinal data is an observed data of some uncorrelated subjects, and each subject was observed for some periods. This research developed a nonparametric regression approach for longitudinal data by using Fourier series. One of the advantages of Fourier series is it combines additive that is able to overcome the data with recurrent and high fluctuations. The research use data with 3 subjects and 128 observations. The Fourier model by combining additive linear functions and cosine functions is more suitable for modeling repeated data that has an element of trend, as the 2nd sector.
Modelling rice production in Central Java using semiparametric regression of local polynomial kernel approach
Authors: Utami T W , Prahutama A , Karim A , Achmad A R. F 
Published: June 2019

Abstract
Indonesia is an agricultural country with rice as one of the staple foods. Production of rice in the province of Central Java is the highest in Indonesia. The purpose of this study was to model rice production in 31 districts / cities in Central Java Province using semiparametric regression. Semiparametric regression is a combination of parametric and nonparametric regression. Parametric regression curves have a patterned, for example linear, quadratic, and cubic. Nonparametric regression has a smooth curve of the unknown pattern, so in this case required smoothing technique used to smooth curves that one of them is the local polynomial kernel approach and the election of bandwidth the optimal using method Generalized Cross Validation (GCV). Variables used in the study of the production of rice as the response variable, while the predictor variables that harvested area and rainfall. The data used are secondary data from the official website of Central Bureau of Statistics (BPS) of Central Java. Based on the results obtained by applying the model the optimal bandwidth values is 0.43 and polynomial order p = 2 when the minimum GCV so the results of the estimation model R2 is 0.968
Extreme rainfall prediction using spatial extreme value by Max Stable Process (MSP) Smith model approach
Authors: Yasin H , Hakim A R , Warsito B , Santoso R 
Published: June 2019

Abstract
This research covers Spatial Extreme Value method application with Max-Stable Process (MSP) approach that will be used to analysis Extreme Rainfall in Semarang city. Extreme value sample are selected by Block Maxima methods, it will be estimated into Spatial Extreme Value form by including location factors. Then it transform to Frechet distribution because it has a Heavy tail pattern. Max Stable Process (MSP) is an extension of the multivariate extreme value distribution into infinite dimension of the Extreme Value Theory. MSP using Generalized Extreme Value (GEV) approach, it has three forms distribution that is Gumbel, Frechet and Weibull. Extreme Value Samples that are selected by Block Maxima will follow GEV distribution. The best model that obtained based on Max-Stable with Smith model can be used to predict Extreme Rainfall by count Return Level. Then can be further analysis of various aspects, so it can provide a suggestion about the potential of natural disasters which are caused by extreme rainfall. Extreme rainfall prediction using the Smith model in the return period of the next two years, at the Semarang City Climatology, Tanjung Mas and Ahmad Yani Station is predicted to be a maximum of 100.7539 mm, 100.1052 mm, and 109.9379 mm.
The shortest path search application based on the city transport route in Semarang using the Floyd-warshall algorithm
Authors: Khamami A , Saputra R 
Published: June 2019

Abstract
City transportation is a motorized vehicle with a fixed line that connects one area to another in one city. Information about the city transportation route in Semarang has been provided by the Department of Transportation of Semarang city which contains the code and route. The development of science regarding the route search algorithm method or the shortest path can be used to support the path search based on the city transportation route. A geographical information system is a system designed to work using data that has spatial reference spatial information. At this time the technology has not been applied optimally to support the search for the shortest route of urban transport based on the city transportation route. This study aims to develop the application of the shortest pathway determination based on the city transportation route in Semarang using the Floyd Warshall algorithm based on Geographic Information System. City transportation route data can be implemented in graph form. The process of establishing a path graph is based on the road protocol traversed by Semarang city transportation. In this research, Floyd-warshall algorithm was successfully implemented in the Shortest Path Determination Application based on the City Transport Route in Semarang. Based on the results of testing the Floyd Warshall algorithm calculation by comparing manual calculations and calculations generated by the application, producing the path with the shortest distance the same so that the application gives the correct results. The results of usability testing which include aspects of ease, efficiency, easy to remember, errors and satisfaction in this application get a percentage overall 92,9% with very good qualification results. This application displays route maps. codes and trip descriptions from the initial position and destination position that can be selected by city transport users in Semarang
Clustering student behavior based on quiz activities on moodle LMS to discover the relation with a final exam score
Authors: Waspada I , Bahtiar N , Wibowo A 
Published: June 2019

Abstract
One strategy in using the Learning Management System (LMS) is to provide activities that can be accessed by students as learning material. The problem is that the teacher cannot see the students’ online activity directly. In this study, the students’ behavior was discovered from the e-learning log file on the quiz activity. Quis activities are performed six times and end with a final exam. Four attributes were proposed as the student behavior model, they are the frequency of repeating quiz work (freq), the duration on each quiz work (our), increased score when repeating the quiz (perf), and the best score of all attempts (best). The preferable clustering result using K-means algorithm was obtained with 2 (two) clusters. Each cluster was paired with the final exam score which shows that the percentage of failures in cluster_0 is 85%. This result corresponds to the centroid value in cluster_0 that is lower in all attributes compare to the cluster_1. It concludes to evidence that the activity of working on online quizzes has a relation with the final exam score. This information can be used for early intervention by the teacher to prevent the student from failing.