bluuebunny/crossref_metadata_2025_split huggingface dataset:
Isolation and molecular identification of thermophilic bacteria from litter of mount Galunggung hot spring, Tasikmalaya, Indonesia
Authors: Ningsih F , Nurlaili D G , Yokota A , Yabe S , Sjamsuridzal W 
Published: July 2021

AbstractThermophilic bacteria from litter deposited at Cipanas hot spring of mount Galunggung, Tasikmalaya, West Java, Indonesia, were isolated using a culture-dependent approach. Medium InternationalStreptomycesProject (ISP) 1 solidified with gellan gum was used as an isolation medium. Isolation plates were incubated at 50°C for three weeks. The physicochemical analysis showed that the hot spring has a neutral pH and temperatures ranging from 50−56°C. A total of 16 bacterial isolates were obtained and purified. The analysis of partial 16S rRNA gene sequences data and phylogenetic analyses showed that they belong toFirmicutesandProteobacteriaphyla. The majority of bacterial isolates are spore-forming bacteria. The molecular identification based on the 16S rRNA gene sequence data showed that they belong toAneurinibacillus thermoaerophilus(1);Brevibacillus gelatini(7);Bacillus licheniformis(1);Chelatococcus composti(1);Laceyella sacchari(2);Paenibacillus barengoltzii(1); andPseudoxanthomonas taiwanensis(3). Percentage sequence similarities to their closest taxa were 91 to 99%. Phylogenetic analysis shed a light to the detection of candidates of novel taxa from litter of mount Galunggung hot spring.
Production of γ- Aminobutyric Acid (GABA) by Monascus Purpureus isolated from Angkak, a mold isolated from Angkak in Semarang, Indonesia
Authors: Kusdiyantini E , Nurhayati  , Ferniah R S 
Published: July 2021

Abstract
Angkak is a rice fermented product that has red colour because of the presence of Monascus sp. This product has long been used as a food colouring and traditional medicine, especially in Asian countries including Indonesia. Angkak is also commercialized in Semarang and used as a medicine for dengue fever. Monascus purpureus is a common mold obtained from Angkak marketed in Semarang. In addition to producing pigments for food, Monascus sp. can synthesize lovastatin or monacolin-K which could reduce blood cholesterol levels also produce γ-aminobutyric acid (GABA) which has physiological functions, such as neurotransmitters. This study aimed to determine the production of GABA produced by Monascus purpureus isolated from commercial Angkak in Semarang. M. purpureus was grown in broth medium (Potato Dextrose Broth) for 14 days in 28°C, and regularly measured the pigment concentration and GABA content every 6 days. The mould was also cultivated in rice solid medium (IR42) for 30 days to measure GABA concentration. The result showed that extracellular pigments were yellow and red with concentration for about 37,358 U/g and 2.6545 U/g, respectively. While intracellular pigment stored in mycelia, the yellow pigment had the highest concentration (30.176 U/g) followed by yellow pigment (7.1475 U/g). GABA content obtained from a broth culture of M. purpureus, Angkak from M. purpureus and commercial Angkak were 0.0796 mg/mL, 0.0332 mg/mL and 0.0203 mg/mL, respectively.
Automatic speech recognition by using local adaptive thresholding in continuous speech segmentation
Authors: Endah S N , Kusumaningrum R , Adhy S , Ulfattah R A 
Published: July 2021

Abstract
Speech recognition of continuous speech will be greatly influenced by the word segmentation process of the speech input. Proper segmentation will result in better speech recognition. This study proposed automatic speech recognition by applying local adaptive thresholding in the segmentation process. The segmentation method used is an enhanced blocking block area method whose input is a spectrogram image of the speech signal. While the locally adaptive thresholding method used is the Niblack method which is the best method compared to other methods, namely Sauvola, Bradley, Guanglei Xiong, and Bernsen when applied to the enhanced blocking block area method. For the speech recognition process, using Mel-frequency cepstral coefficients (MFCC) as a feature extraction method and Hidden Markov Model (HMM) as speech recognition. The experimental results show that by using 400 sentences consisting of 80 testing data and 320 as training data and using K-fold cross-validation, the highest accuracy is 60,8%. This result has no significant difference with the use of global thresholding in the segmentation process.
Analysis of factors that influence satisfaction and usefulness for attendance system with the Delone & McLean model (case study: attendance system at Diponegoro University)
Authors: Nugraheni D M K , Bayastura S F 
Published: July 2021

Abstract
The attendance system is an educational management tool at Diponegoro University used for attendance activities using technology. The attendance system is implemented in the “Sistem Informasi Akademik, Penelitian dan Pengabdian” (SIAP) application and can be accessed by students through Single Sign On (SSO). Students can do it using the smartphone they have. This research is analyzed through the factors that affect students’ satisfaction and usefulness after using the attendance system. The analysis will be performed using the Delone & McLean model and additional usefulness variables from the Technology Acceptance Model (TAM) model. A total of 506 respondents participated in this research. Respondent data is then processed using smartPLS 3.0 software. Based on the research, some indicators do not meet the measurement criteria. The attendance information on the attendance system can be accessed using various types of smartphones, so the indicators must be removed from the model. The research results have found that system quality affects usefulness, service quality effect on usefulness, information quality effect on usefulness, system quality effect user satisfaction, service quality effect on user satisfaction, information quality affect on user satisfaction, and usefulness effect on user satisfaction.
Fisheries waste handling to enhanced fishers society economic growth: blue growth initiative perspective
Authors: Dewi D A A N , Sugiyanto F X , Iskandar D D 
Published: July 2021

Abstract
Residual waste processing is an alternative to enhance coastal communities capabilities. This is one of the blue growth initiative programs. Fisheries waste forms are heads, bones, scales, fish entrails, or shells. The purposes of this observation are to provide an alternative way to handling waste produced by scallops to reduce waste, calculate waste treatment product, processing waste shell value and estimate waste processing revenue. The research method uses quantitative descriptive method with a case approach to the management of scallops waste shells in Batang District in Central Java Province. Production of scallop shells in Batang District which can be processed into Ca flour is estimated as much as 9.17 tons per year. Gross income approximately IDR 45,788,080.00 per year. It is an alternative product as a community side job around the shellfish waste landfill area and resolves the problem of shell waste in Batang District.
Mathematical model of ships convoy in delivery of goods
Authors: Tjahjana R H 
Published: July 2021

Abstract
This paper describes the ship convoys intended for mathematically modelling. The phenomenon essentially imitates the behaviour of a shoal of fish for several advantages. However, a control design is investigated to ascertain the factors influencing the fleet to navigate jointly without diversion or collision. Furthermore, the vessels are assumed to function independently, but are only assigned a common task of delivering goods. The control design process employs an optimal method known as the Pontryagin Maximum Principle, and the model implemented is generally applied to marine vessels. Meanwhile, the control equation utilizes the Nomoto’s model. In addition, the ship model supports the rudder input responsible for the change in the direction of motion. Also, this study exposes a functional cost pattern describing the joint tasks and further models the ship convoys for optimum control. The numerical simulation provides a detailed summary of the applied optimal process to solve the problems encountered in deliveries.
Properties of the matrix from Kronecker product on the representation of quaternion group
Authors: Ahsan  , Yanita Y , Bahri S 
Published: July 2021

Abstract
This paper discusses the properties of matrices, which are elements of a group derived from the application of Kronecker product to the representation of the quaternion group (the author calls this group with Kronecker quaternion group). The properties of the new matrices constructed by matrices from the Kronecker quaternion group as submatrix in a partitioned matrix are discussed based on transpose, determinant, and permutation matrix.
Fuzzy time series Markov Chain and Fuzzy time series Chen & Hsu for forecasting
Authors: Zaenurrohman  , Hariyanto S , Udjiani T 
Published: July 2021

Abstract
Fuzzy time series theory is a concept of artificial intelligence that can use to conduct forecasting technique.. This paper discusses the fuzzy logic concept to develop the base of the fuzzy time series with time invariant and time variant methods. There are several methods of fuzzy time series, including Markov Chain method and Chen and Hsu method. The Markov Chain method combines between the fuzzy time series and the Markov Chain. This merger goals to finest opportunity of the use matrix probability transitions. Chen and Hsu method is based on the historical data difference in conducting forecasting. By using Markov Chain and Chen & Hsu methods, it may achieve forecasting outcomes with a low mistakes rate. To clarify each technique and for comparison further, it is given an example of the relevant issue to be resolved by both methods. The consequences acquired can be compared, so it can be concluded which method is better.
The time series clustering of stock price in LQ45 index and its financial performance analysis
Authors: Afrimayani  , Devianto D 
Published: July 2021

AbstractStock price in time series data can be analyzed with the clustering method by using the autocorrelation function distance measurement method. The purpose of this study is to cluster stock prices with the same characteristics and analyze companies’ financial performance in each cluster and provide a reference to investors in making choices to develop their investments. This study uses time-series data from stock prices in the LQ45 index, which is continuously available and registered from January 2010 to December 2019, as many as 32 companies. The results of this study are obtained 3 clusters, where the first cluster contains 17 stocks, the second cluster contains six stocks, and the third cluster contains nine stocks. After clustering, the financial performance of each cluster is analyzed in 2019. The companies’ financial performance in the first cluster shows that the company has proper inventories, total assets, profit for the period, and can get great benefits. The third cluster shows that the company has a relatively good current ratio and demonstrates its ability to generate profits from the high assets and equity used. Meanwhile, the second cluster has quite high receivables.
Application of Fuzzy AHP and Fuzzy TOPSIS methods for the new normal problem
Authors: Utomo E Y , Udjiani T , Surarso B 
Published: July 2021

Abstract
The government have new program to deal with the pandemic impact of the Coronavirus, which is said with the new normal. The implementation of the new normal itself requires more attention in terms of the readiness of a region to implement the program. Determination of these areas can be done using the Fuzzy Analytical Hierarchy Process(AHP) and fuzzy technique for Order Performance by Similarity to Ideal Solution(TOPSIS) methods. Fuzzy AHP is used to determine the weight of the existing criteria, while Fuzzy TOPSIS is used to determine the safest area and is ready to implement the new normal. The case study for the problem in this paper is Central Java Province, with alternatives districts and cities. The influencing criterias are the number of People Under Surveillance (PeUS), the number of Patient Under Surveillance (PaUS), the number of patients being treated, the number of positive patients who died, and positive patients who recovered. Triangular fuzzy number approach both methods. The results of this study found that 30% of the total number of districts or cities are ready to implement the New Normal program. This study also explain that the higher of the patient number being treated, the less safe an area will be. While the patients number who recover is increasing, then an area will be ready to implement a New Normal program.
Local stability analysis for tuberculosis epidemic with SI1I2R model
Authors: Taqiya F A , Sutimin  , Tjahjana R H , Utomo R H S , Herdiana R , Permatasari A H 
Published: July 2021

Abstract
TB is an infectious disease that attacks parts of the body, one of the lungs. This disease is caused by the bacterium Mycobacterium Tuberculosis through the droplet nucleus which spreads when the patient coughs or sneezes. This TB epidemic model is classified into four subpopulations, namely the susceptible subpopulation, the symptomatic infection subpopulation, the asymptomatic infection subpopulation, and the recovered subpopulation, by introducing treatment at each stage of infection and analysing dynamic models. The analysis was carried out to determine the local stability balance point which can be determined through the basic reproduction number (ℛ0) obtained through the Next Generation Matrix (NGM). When the value of ℛ0 <1, the disease-free equilibrium point will be asymptotically stable using the Routh-Hurwitz criteria, and when ℛ0> 1, the endemic equilibrium point will be asymptotically stable locally using the Manifold Center. The Routh-Hurwitz criterion is used to investigate the stability of the disease-free equilibrium point if all parts of the real eigenvalues of the jacobian matrix are negative. The manifold center method is used to investigate the stability of the endemic equilibrium point at ℛ0> 1 which is determined by the number of roots of the characteristic equation with zero root real parts. Numerical simulations are used to make it easier to explain the dynamic behavior of a system and describe its analytical results.
Individual self-development information system based on the evaluation of civil servant performance appraisal with ELECTRE method and profile matching
Authors: Pertiwi A N F I , Surarso B , Farikhin  
Published: July 2021

Abstract
Improvement Performance Appraisal of the Civil Servant (CS) is important in the field of Human Resource Development. Currently, conventional performance appraisal is still used even though it cannot provide an objective assessment. CS performance is important so it needs to be properly assessed. CS performance is influenced by working behavior and competence. Various methods have been carried out to improve the competence of CS. In this case, more directed to a formal way, Self-Development is less emphasized on each individual CS itself. Therefore, in this research, Profile Matching and ELECTRE method is recommended to measure the value of criteria weighting on CS Self-Development. Input from this Profile Matching are questioner data in the form of interest and talent ability from CS. Then the suitable measurement is used to determine the weight criteria using ELECTRE. Thus, the ELECTRE method will be used to calculate the values that have been obtained and adjusted to the existing rules. The output of this information system is a data list of recommendations for field competencies that can be selected by CS.
Convergence of the 3-point block backward differentiation formulas with off-step point for stiff ODEs
Authors: Soomro H , Daud H , Zainuddin N 
Published: July 2021

Abstract
Development of 3-Point Block Method with one off-step point using Backward Differentiation Formula (BDF) is presented in this paper to find out the solution for stiff Ordinary Differential Equation (ODEs). By considering the Backward Differentiation Formulas (BBDF), the block method has been derived. It is well known that BBDF is used for solving stiff ODEs. The strategy for the development of this process is to compute three solution values with one off-step point concurrently to each iteration. One off-step point is added in the implicit BBDF method for better accuracy. Derivation of the formulae and consistency properties are generated in this paper. Numerically the proposed method with order five is achieved as a result. Mathematica software has been used for the derivation and consistency of the method.
Tchebycheff system and its application to construct the minimally supported design for generalized exponential model
Authors: Widiharih T , Mustafid  , Sudarno  , Prahutama A 
Published: July 2021

Abstract
The generalized exponential model has a unimodal curve shape, so it can be used as a growth function model. Determination of the supported designs must be run to construct the model is a serious problem. Based on the supported designs are expected to meet the optimal criteria. In this paper, we use the D-optimal criteria, which is minimized the variance of the parameter estimator. The standardized variance function has an important role in the D-optimal design. The D-optimal design is a design with the value of standardized variance at supported designs is equal to the number of parameters. The number of roots of the standardized variance function needs to be find to determine the number of supported designs. Tchebycheff system is a set of continuous functions that can be used to determine the number of roots of a function. A design with the number of supported designs same as the number of roots of the standardized variance function with uniform weight is a minimally supported design.
Robust regression with MM-estimator for modelling the number maternal mortality of pregnancy in Central Java, Indonesia
Authors: Prahutama A , Rusgiyono A 
Published: July 2021

Abstract
Regression is a method of statistics analysis for modeling between the dependent variable to independent variables. Estimation in the regression model uses the Ordinary Least Square (OLS) method. In the regression model, several assumptions are required. One of the reasons for the violation of the assumption is that there are outliers in the data. There are several methods that can be used to overcome outliers, one of which is using the Robust MM-estimator regression. The MM-estimator has high efficiency when the error is normally distributed and also has a high breakdown value. To implement the SDG’s program, one program is health. It has objectiveness to reduce maternal mortality rate. Maternal mortality consist of pregnancy, give of birth and postpartum mother. In this study the data used was the number of maternal mortality of pregnancy in Central Java in 2019 as the dependent variable, while the independent variables used included the percentage of pregnant women consuming Fe3 tablet (X1), percentage of households that have a clean and healthy lifestyle (X2); percentage of pregnant women who made the first visit (X3); The results obtained in multiple regression modeling produce R square value of 0.222679 and Mean Square Error (MSE) of 6.894871. The assumptions in the regression model unfulfilled, may be caused by outlier in data. In MM robust regression modeling, the R square value is 0.2695, and the MSE value is 4.989. It shows that robust regression modeling with MM estimator is better than multiple regression.
Determination of non-poison queue system of distribution in the public service sector (case study: Semarang city population and civil registry office)
Authors: Sugito  , Prahutama A , Ispriyanti D , Mustafid  
Published: July 2021

Abstract
The public service sector is a sector that is engaged to serve the interests of the community. To get to the public service sector that satisfies the public, there needs to be innovation in system renewal. Many factors need to be analyzed in the public service sector to create a satisfying service. One of the factors determining community satisfaction is the queuing system in the public service area. Queue analysis is an analytical method to measure the performance of a queuing system. The system measured in services includes the number of visitors entering the queue system and the time customers start serving. The queuing system follows the Poisson, Exponential, Normal, or General distribution. For general distribution can be studied into Non-Poisson distribution. In this study, an analysis of the queuing system at the Department of Population and Civil Registration in the city of Semarang included 8 counters. From the analysis results obtained, the general distribution determined is the Dagum and Log Normal distribution. While the size of the performance of the queuing system can be said to be good, because the waiting time for customers in the system is very less.
Analysis of geometric and weibull queuing model (case study: customer service and electronic ID card recording counters at Dispendukcapil of Semarang City)
Authors: Sugito  , Prahutama A , Mustafid  , Ispriyanti D , Dewi L N 
Published: July 2021

Abstract
Semarang is the Capital City of Central Java which has a large population. For 2019, the population has increased from the previous year so that it will cause a change in population identity data. Dispendukcapil of Semarang City is one of the executors of public administration services in Central Java whose task is to carry out affairs in the field of population and civil registration. However, the queue has become one of the problems that occur there because of the arrival of many customers at the same time and is random. So one way to reduce queuing is to apply queuing theory to the system. The queue theory was developed to determine the queuing model so that it can be used to calculate system performance. In measuring the performance of the system determined using Graphical User Interface (GUI) R. The queue model that has been obtained at Dispendukcapil counters in Semarang is customer service counter (Geometric/Weibull)/1):(GD//∞/∞) and electronic ID Card recording counter (Geometric/Weibull)/1):(GD//∞/∞).
The use of statistical transformation in six sigma analysis
Authors: Mustafid  , Yulvia I , Ispriyanti D , Sugito  , Hakim A R 
Published: July 2021

Abstract
The basic assumptions in six sigma analysis are use data assumptions from the quality characteristic variables in-control and normal distributed. The use of normal distribution assumptions aims to facilitate the computational and analytical processes. In fact, there are many observational data obtained from industry which are uncontrolled and not normally distributed. The aim of the research is to use exponentially weight moving average (EWMA) as statistical transformation to make data uncontrolled and not normally distributed into data in-control and normal distributed. This research uses a case study with empirical data Weibull distributed, and use the statistics of EWMA to the data can be transformed into in-control and normal distributed. Based on the results of the transformation from empirical data, the EWMA control chart were made to determine the data position of in-control and also measured six sigma values.