bluuebunny/crossref_metadata_2025_split huggingface dataset:
Market basket analysis using apriori algorithm to find consumer patterns in buying goods through transaction data (case study of Mizan computer retail stores)
Authors: Qisman M , Rosadi R , Abdullah A S 
Published: January 2021

Abstract
Mizan Computer Shop is a shop that is engaged in the trading sector, especially in the field of selling computers and supporting accessories. Growing and increasing number of business actors in the computer sector, can makes the players challenged to be able to create unique differentiation and clear positioning. So, that consumers can differentiate from their competitors. Competitive and dynamic market conditions make every company should always observe competition in their business environment. Retail stores need to use all of available resources including data. Data processing is expected to be able to provide information that can be used to support marketing strategies. One of the data processing methods that are often used in marketing strategies is the use of data mining techniques i.e Market Basket Analysis using a priori algorithm. The application is designed using the waterfall method which starts from analyzing user needs, designing a process using UML which consists of: Use Case Diagrams, Activity Diagrams and Sequence Diagrams . This Market Basket Analysis application was built using the PHP programming language. From the results of the analysis in this research, it can be concluded that for the combination of 2 items with the highest confidence value 100% and the lift ratio value 3.39 i.e if a consumer buys a Laptop Charger, he will also buy a keyboard and for a combination of 3 items with the highest confidence value 100% and the lift ratio value 2.17 i.e if a consumer buys a Joystick and Laptop, he will also buy a mouse.
The construction of real Frobenius Lie algebras from non-commutative nilpotent Lie algebras of dimension
Authors: Kurniadi E , Carnia E , Supriatna A K 
Published: January 2021

Abstract
In this present paper, we study real Frobenius Lie algebras constructed from non-commutative nilpotent Lie algebras of dimension ≤ 4. The main purpose is to obtain Frobenius Lie algebras of dimension ≤ 6. Particularly, for a given non-commutative nilpotent Lie algebras N of dimension ≤ 4 we show that there exist commutative subalgebras of dimension ≤ 2 such that the semi-direct sums ɡ = N⊕T is Frobenius Lie algebras. Moreover, T is called a split torus which is a commutative subalgebra of derivation of N and it depends on the given N. To obtain this split torus, we apply Ayala’s formulas of a Lie algebra derivation by taking a diagonal matrix of a standard representation matrix of the Lie algebra derivation of N. The discussion of higher dimension of Frobenius Lie algebras obtained from non-commutative nilpotent Lie algebras is still an open problem.
Application of the Ordinary Kriging method for prediction of the positive spread of Covid-19 in West Java
Authors: Ruchjana B N , Falah A N , Abdullah A S 
Published: January 2021

Abstract
The Ordinary Kriging method is a method used to predict an observation at an unobserved location based on observed points that are spatially related. Corona Virus Disease 19 (Covid-19) is a contagious disease and viral pathogenic infection caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2). This virus spreads almost all over the world including Indonesia and it gives an influence between location. In this study, a case study was carried out with predictions on the positive distribution data of Covid-19 at 27 districts/cities in West Java. The process of calculating predictions of the positive distribution Covid-19 is started by the determination of the experimental semivariogram model. The Covid-19 data have an Exponential Semivariogram model which is used as an input of the Ordinary Kriging. Furthermore, using the R program for the Ordinary Kriging, we can predict the observation of positive Covid-19 at unobserved locations in West Java.
The behavior of solution function of the fractional differential equations using modified homotopy perturbation method
Authors: Rusyaman E , Parmikanti K , Chaerani D , Supriatna A K 
Published: January 2021

Abstract
The discourse regarding fractional calculus, in particular those related to fractional differential equation, is still continue to attract researcher attention. Previous studies have elaborated on the variation of fractional differential equation models. This study aims to uncover the problem of convergence of the solution function sequence related to the order of fractional differential equation. Firstly, this study presents how to find a solution for the model by using a Modified Homotopy Perturbation Method as the improvement of Homotopy Perturbation Method. Furthermore, the solution function with the sequence of fractional order is drawn by Maple. Using the geometrical analysis, the result of this study shows that if fractional order sequence is convergent to α, then sequence of its solution function will be convergent to a solution function of fractional differential equation with order α.
Analysis of problem-solving difficulties at limits of sequences
Authors: Isnani  , Waluya S B , Rochmad  , Dwiyanto  , Asih T S N 
Published: January 2021

Abstract
Every year, most mathematics education students have difficulty learning real analysis courses on the material of sequences and series, especially in the sub material of the limit of sequences. Difficulties in learning the concept of limits include difficulties in understanding the limit concept’s definition and visualization. The purpose of this article is to analyze the difficulties of mathematics education students of Pancasakti University in the Tegal academic year 2019/2020 in problem solving at limits of sequences and providing appropriate Scaffolding to overcome these difficulties. This research is descriptive qualitative research. The research subjects were selected using the purposing sample technique, selected two students with high, medium, and low abilities. Two students chose each capacity. Interview with research subjects to inform the results of the test using the aloud method. Students experience difficulty thinking when solving the limit of sequences problem due to the lack of initial analysis and student analogy skills. When the procedure is rechecked, students have difficulty thinking too. This is due to the lack of mathematical connection skills of students. To overcome these student difficulties, the lecturer must provide Scaffolding.
Determination distribution route of beverage products with the application of the vehicle routing problem model and sensitivity analysis
Authors: Auliani F , Hertini E , Nahar J 
Published: January 2021

Abstract
Vehicle Routing Problem (VRP) is the problem of determining the optimal route to distribute goods or products using vehicles to some customers. The goals are to minimize the cost and distance of distribution by observing some constraints or restrictions. The problem of determining the distribution route of beverage products in Serang City by a beverage distribution company can be solved by applying the VRP model by considering the vehicle capacity limit. The optimal solution of route determination models is obtained by using Branch and Bound method of the LINGO 18.0. Results showed that the optimal route of distribution with the implementation of the VRP model could minimize the total distribution costs incurred by the company compared to the existing distribution route used by the company. Sensitivity analysis results showed that changes in fuel costs resulted in optimal routes gained by the application of the VRP model could not be sustained, so a new decision was required by the company in determining the distribution route. The reduction in fuel costs resulted in a reduction in total distribution costs and increased fuel costs increased the total cost of distribution.
The odd harmonious labeling of matting graph
Authors: Mumtaz K , John P , Silaban D R 
Published: January 2021

Abstract
Let G(p, q) be a graph that consists of p vertices and q edges, where V is the set of vertices and E is the set of edges of G. A graph G(p, q) is odd harmonious if there exists an injective function f that labels the vertices of G by integer from 0 to 2q − 1 that induced a bijective function f
∗ defined by f
∗(uν) = f(u) + f(ν) such that the labels of edges are odd integer from 1 to 2q − 1. A graph that admits harmonious labeling is called a harmonious graph. A matting graph is a chain of C
4 −snake graph. A matting graph can be view as a variation of the grid graph. In this paper, we prove that the matting graph is an odd harmonious graph.
The Metric-Location-Domination Number of k-Paths
Authors: Zulfaneti  , Baskoro Edy Tri 
Published: January 2021

AbstractLetGbe a connected graph with vertex setV(G) and edge setE(G). For ordered subsetW= {w1,w2…,wk} ofV(G) andv∈V(G), the representation ofvwith respect toWis thek-vectorr(v|W) = (d(v, w1),d(v, w2),…, d(v, wk)), whered(x, y) is the distance between verticesxandy. The setWis called a resolving set ofGif all vertices ofGhave distinct representations with respect toW. A subsetS⊆V(G) is called a dominating set ofGif every vertex ofG\Sis adjacent to some vertex ofS. The cardinality of a minimum dominating set is the domination numberγ(G) ofG. An orderedW⊆V(G) is called a metric-locating-dominating set ofGifWis a dominating as well as resolving set. The metric-location-domination number ofG, denoted byγM(G), is the cardinality of a minimum dominating resolving set. Ak-pathGis the graph with vertex setV(G) = {v1,v2, …,vn} and edge setE(G) = {vivj:|j −i| ≤ k}. In this paper, we determine the metric-location-domination number ofk-path, and in particular, we show that Ifn > k(2k+ 1) thenγM(G) =γ(G).
The autoregressive integrated vector model approach for covid-19 data in Indonesia and Singapore
Authors: Fitriani R , Revildy W D , Marhamah E , Toharudin T , Ruchjana B N 
Published: January 2021

Abstract
Almost all of the countries in the world were attacked by coronavirus disease 2019 (covid-19) which is started from pneumonia endemic cases in Wuhan China in December 2019. The virus spreads including in the Southeast Asian region where Singapore and Indonesia are two countries with the highest cases. Simultaneous modeling of cases in both countries is important as information on the development of covid-19 cases. The Vector Autoregressive Integrated (VARI) model is a multivariate time series model that can be used to build model non-stationary time series data in several locations simultaneously. This study aims to analyze the development of covid-19 cases and builds a VARI model of covid-19 cases in Indonesia and Singapore. The data used from daily covid-19 confirmed cases in the period March 16th until April 19th, 2020. Plotting and statistics testing covid-19 data series from both countries show non-stationary series which have trend and fluctuation. Based on optimum lag identification use the minimum Akaike Information Criteria correction (AICc), the parsimony model is obtained namely VARI(1,1) which has satisfied the multivariate normal, white noise, and homogenous assumption. The result shows that covid-19 cases in Indonesia and Singapore have a strong positive correlation. However, the covid-19 cases in both countries were only influenced by previous cases in each country. The accuracy shows that the model is good enough for forecasting covid-19 cases in both countries.
Modeling of covid-19 in Indonesia using vector autoregressive integrated moving average
Authors: Meimela A , Lestari S S S , Mahdy I F , Toharudin T , Ruchjana B N 
Published: January 2021

Abstract
A phenomenon of coronavirus became a big deal around the world at the end of December 2019. To find out how deadly the disease is, we can use the Case Fatality Rate (CFR), which provides the ratio number of deaths due to covid-19 between founded cases number of covid-19. However, studies to see the relationship between the number of cases and the number of deaths caused by covid-19 in Indonesia rarely done. Time Series analysis that can see how the relationship between the number of cases and the number of deaths due to covid-19 in Indonesia is Vector Autoregressive Integrated Moving Average analysis (VARIMA). Data used in this model must be qualified the stationary. For that reason, the transformation using differencing and logarithm on data must be performed to resolve non-stationary. The result shows the model that fulfilled all assumptions and had the smallest AICC value is VARIMA (1,1,1). The model shows the number of cases influenced by the number of cases and the number of deaths in the previous period. The same condition applies to the number of deaths affected by the number of deaths and the number of cases from the preceding period.
Geographically weighted models for modelling the prevalence of tuberculosis in Java
Authors: Noorcintanami S , Widyaningsih Y , Abdullah S 
Published: January 2021

Abstract
Indonesia’s position as one of the high burden countries for the infectious disease, tuberculosis (TB), has caused TB to be a major health problem in Indonesia. As means to control the number of TB cases, it becomes important for the government to identify factors associated with it. Commonly, multiple linear regression models are used to evaluate the linear relationship between the identified factors and the number of TB cases. Unfortunately, this model does not have the ability to expose the spatial variation in the data. Therefore, this study proposes to implement a spatial model: a model that takes the geographical location in the model. This research examined two types of geographically weighted models (GWM): geographically weighted regression (GWR) and mixed geographically weighted regression (MGWR). These spatial models assign weights to observations based on its’ geographical location. These two models were constructed to evaluate the relationship between the prevalence of TB in regency/city in Java in 2017 and the factors associated with it: population size, success rate of TB treatment, percentage of toddlers receiving BCG vaccine, percentage of HIV patient, percentage of household with adequate sanitation, percentage of poor people and the number of public health centre per one hundred thousand people. Akaike’s Information Criterion (AIC) and adjusted R2 were used to assess the model performances. We found that the GWR model fits the data better than MGWR, as it has a smaller AIC value (1558.67) and a higher adjusted R2 (0.754). It is also found that BCG vaccine is important to reduce the prevalence of TB, as the percentage of toddlers receiving BCG vaccine is negatively associated with it. Among the examined areas, Jakarta is the area with the highest association between the percentage of toddlers receiving BCG vaccine and the prevalence of TB.
Empirical evaluation on discounted Thompson sampling for multi-armed bandit problem with piecewise-stationary Bernoulli arms
Authors: Asyuraa F C , Abdullah S , Sutanto T E 
Published: January 2021

Abstract
The Multi-Armed Bandit problem is a problem in reinforcement learning that focuses on how to solve the exploration-exploitation dilemma. The dilemma is, given a set of options (known as arms) that you could try many times, how to balance between gathering information through experimenting with the available arms (exploration) or maximizing profit by choosing the seemingly best arm at that time (exploitation). The Multi-Armed Bandit problem is centered around determining which arm to choose at every round. Multi-Armed Bandit has gained its popularity as a more dynamic approach to a randomized trial, with its goal is to experiment with each available arm while still maximizing profit gained. An example of Multi-Armed Bandit in real life is in determining which film artwork should be shown to a visitor that would attract the visitor to watch that particular film. Bernoulli distribution with parameter θ is chosen to model the response of the visitor after seeing the artwork. Non-stationary condition on θ can be implemented to accommodate various trends in film artworks. Some artworks might be good at a certain month, but they could not be preferred in the next month. The non-stationary condition in this study is modeled through piecewise-stationary. We implemented a discounted Thompson sampling policy that used Bayesian method to determine which arm to choose at each round. Multiple simulations were conducted on various conditions to empirically test the policy’s performance on various conditions. Evaluation was based on the cumulative regret. Based on these simulations, discounted Thompson sampling policy achieved relatively lower cumulative regret in tackling the stationary and piecewise-stationary conditions, compared to some well-known policies such as Epsilon Greedy, SoftMax, Upper Confidence Bound, and Thompson Sampling.
Bayesian MSTBurr mixture model in the construction of 3D-MRI brain tumor images
Authors: Pravitasari A A , Iriawan N , Fithriasari K , Purnami S W , Irhamah  , Ferriastuti W 
Published: January 2021

Abstract
Detection of a brain tumor could be done with the serial of MRI images. The location and size of the tumor should be determined by viewing the 2D images individually. This kind of analysis is inefficient and error-prone. For better visualization, this study reconstructs a 3D structure from 2D MRI images. In recognizing the brain tumors, image segmentation is performed using the clustering analysis via Bayesian MSTBurr Mixture Model. The optimum cluster is selected by calculating the Correct Classification Ratio. The segmentation results for each image slice are performed in 3D rendering with the Matlab Volume Viewer. This study succeeded in creating a 3D model with a segmentation accuracy of 93.66% and an estimation of the tumor volume of about 33,556 mm3.
Designing PISA-like task on uncertainty and data using Covid-19 context
Authors: Zulkardi  , Nusantara D S , Putri R I I 
Published: January 2021

Abstract
COVID-19 pandemic is an example of a global context and real-world phenomena. This context is an excellent example of the uncertainty and data, a part of the content knowledge in the PISA 2021 framework. This new content of the uncertainty and data as a part of mathematics literacy focuses on conditional decision-making. This paper aims at sharing the development and implementation of the PISA like task using three steps of design research method. Firstly, a preliminary study on the history and development of PISA in Indonesia. Then, the PISA-like items’ design process continued with the tasks’ experiment using focus group discussion. In the end, the PISA problems have resulted after a formative evaluation. Finally, it is produced valid and practical of three PISA-items and had a potential effect on students’ mathematical literacy.
The implementation of the discovery model based on numbered head together reviewed from students’ cognitive style in mathematics learning
Authors: Setyaningsih N , Utami D P 
Published: January 2021

Abstract
Students consider that mathematics learning delivered by the teacher to be very boring, teacher-centered learning and most students said that mathematics difficult to understand. For this reason, this study aims to analyze the implementation of the discovery model based on NHT in mathematics learning in terms of students’ cognitive styles. This study uses a quantitative approach with a quasi experimental research design. The population in this study were all 7th grade students of SMP Karangmalang Sragen. The sampling technique in this study was using cluster random sampling technique. Meanwhile, the data analysis technique used two-way analysis of variance. The results showed that there were differences in the achievement of mathematics learning outcomes in terms of the use of learning models and students’ cognitive styles.
Malodorous Gas Sensor Array System for the Olfactory Robot
Authors: Zhang Xu , Zhang Sixiang , Ma Xu 
Published: January 2021

Abstract
Malodorous gas sensor array system for the olfaction robot is developed with four sensors including two semiconductor metal oxide sensors, a electrochemical sensor and a photoionization detector (PID). The system structure and experiments analysis are introduced in this paper. Result of experiments show that the steady system can keep ±0.03V fluctuation limited from 0 to 5 V after it stabilized and the maximum difference of response less than 0.02V. It means that the developed system can be satisfied for the olfaction application of robots in malodorous environment.
Research on Robot Trajectory Planning Strategy for Water Polo Confrontation
Authors: Wang Chao , Xu Yuefan , Li Hongyang 
Published: January 2021

Abstract
In the multi-joint robot water polo competition, it often occurs that the robot fish glances off the ball when pushing it due to the water waves generated by the fish swimming and the influence of the opponent fish’s attack behavior on the target ball. In order to improve the success rate of the robot fish hitting the ball, this paper proposes a long-distance posture adjustment strategy and double-fish alternative attack strategy. The long-distance posture adjustment strategy is based on the detailed division of the relative positions of the fish, the ball and the goal. The probability of the fish, the ball and the goal being in a three-point line is improved by setting the distance through which the fish body reaches the preset hitting point and the posture adjustment strategy. Besides, the double-fish alternative attack strategy is proposed on the basis of this ball-pushing strategy. The cooperation between the two fishes is strengthened by developing another fish’s returning strategy during the opponent fish hitting the ball, thereby improving the attack efficiency. The experimental results show that the underwater robot fish can avoid the close touch-ball and can attack the ball into the goal more quickly and accurately.
A stable feature selection method based on relevancy and redundancy
Authors: Shen Peng , Ding Xiaoming , Ren Wenjun , Liu Shu 
Published: January 2021

Abstract
In this paper, the characteristics of software defect prediction are analyzed from the perspective of machine learning. To solve the problem of some redundant or uncorrelated features in defect data sets, a stable feature selection method based on relevancy and redundancy (RRSFS) is proposed. RRSFS combines the redundancy between features and the correlation between features and classes to select the optimal subset. RRSFS not only reduces the cost of data operation in the prediction model, but also enhances the stability of feature selection algorithm.
Research on Chinese Event Extraction Method Based on HMM and Multi-stage Method
Authors: Zhan Liying , Jiang Xuping , Liu Qian 
Published: January 2021

Abstract
The existing Chinese event extraction methods are mostly one-stage methods. Even if there are two-stage methods, the correlation between the stages is not high, the extracted event trigger words and event elements have low matching degree, and there is a class imbalance problem in the training process. This paper proposes a Chinese event extraction method based on HMM and multi-stage method. The first stage of the method recognises the event trigger word positive examples in the text; the second stage classifies the trigger word positive examples recognised in the first stage, determines the event type, and forms the sequence of event trigger words; the third stage matches the event elements, and forms the sequence of event elements, according to the first two stages of event trigger word extraction results. This method effectively alleviates the class imbalance problem in training, improves the matching degree between event trigger words and event elements extraction, and obtains better extraction performance. The accuracy, recall rate and F value of Chinese event extraction are all More than 78%.