bluuebunny/crossref_metadata_2025_split huggingface dataset:
Jacobson graph over Z
n
Authors: Aditya Mochammad Zulfikar , Alamsyah Intan Muchtadi 
Published: January 2021

Abstract
Let n ≥ 2. A Jacobson graph over ℤ
n
is a graph with vertex set all elements in ℤ
n
except elements in its Jacobson radical, and x and y are adjacent if and only if 1 − xy is not relative prime to n. In this paper, we give a characterization of Jacobson graph over ℤ
n
as a foundation for Jacobson graph over a finite commutative ring.
Total edge irregularity strength of triple book graphs
Authors: Ratnasari L , Wahyuni S , Susanti Y , Palupi D J E 
Published: January 2021

Abstract
Let G(V, E) be a finite, simple and undirected graph with a vertex set V and an edge set E. An edge irregular total k-labeling is a map f : V ⋃ E → {1, 2, …, k} such that for any two different edges xy and x′y′ in E, ω(xy) ≠ ω(x′y′) where ω(xy) = f(x) + f(y) + f(xy). The minimum k for which the graph G admits an edge irregular total k-labeling is called the total edge irregularity strength of G, denoted by tes(G). We have constructed the formula of an edge irregular total k-labelling and determined the total edge irregularity strength of book graphs and double book graphs. In this paper, we construct an edge irregular total k-labeling that can be used for book graphs, double book graphs, and triple book graphs. We also show the exact value of the total edge irregularity strength of triple book graphs.
Application of linier fuzzy multi-objective programming model in travelling salesman problem
Authors: Hertini E , Nahar J , Supriatna A K 
Published: January 2021

Abstract
Traveling salesman problem is a problem where a salesman must visit a number of cities, each of which is visited exactly once only, and has to start from and return to the origin city. The objective of this traveling salesman is to determine an optimal travel route by minimizing travel cost or travel distance. If a decision maker wants to determine an optimal route by minimizing travel cost and distance simultaneously, they need more than one destination function, and therefore traveling salesman problem can be formulated as a multi-objective problem. In a traveling salesman problem, salesman make decisions by choosing an optimal route based on an expected measurement. In fact, a number of real problems cannot be expressed as a constraint function and resources in a definite form, so it is necessary to use fuzzy logic which allows us for making decisions based on bias or incorrect data. This paper will discuss a solution to the traveling salesman problem by using a fuzzy multi-objective model, which aims to determine an optimal route of the salesman. Results obtained from data processing of five places to visit by using a Maple 18 software included minimum cost, distance, and time with satisfaction level α = 0.89.
Quadratic embedding constants of hairy cycle graphs
Authors: Irawan W , Sugeng K A 
Published: January 2021

AbstractThe quadratic embedding (QE) class of the connected graphG= (V,E) is determined based on its quadratic embedding constant (QEC) of the distance matrix graphG. The distance matrix is a conditionally definite negative, or equivalently if it admits a quadratic embedding in a Hilbert space, or if QEC of the graphGis non-positive. In this study, the classification for the hairy cycle graphs such as bearded cycle graphBC(k,m)forkis even, bearded cycle graphBC(3,m)and broken sun graphBC(4,m)will be calculated, and we derive the formulae of its QEC. These classes of graphs belongs to the QE class.
Infinite Family of Ramsey (K
1,2, C
4)-minimal Graphs
Authors: Hadiputra F. F. , Silaban D. R. 
Published: January 2021

Abstract
Suppose F, G, and H be simple graphs. We let F → (G, H) denote red-blue coloring of edges of F containing either red G or blue H. The graph F is considered Ramsey (G, H)-minimal if F → (G, H) and F − e ↛ (G, H) for arbitrary edge e of E(F ). The set of (G, H)-minimal graphs is denoted by R(G, H). In this paper, we study an infinite family of graphs belongs to R(K
1,2, C
4).
On d-local strong rainbow connection number of prism graphs
Authors: Nugroho E , Sugeng K A 
Published: January 2021

Abstract
A u − ν rainbow path is a path that connects two vertices u and ν in a graph G and every edge in that path has a different color. A connected graph G is called a rainbow graph if there is a rainbow path for every pair of vertices in G. For any two vertices u and ν in G, a rainbow u − ν geodesic in G is the shortest rainbow u − ν path. The d-local strong rainbow number (lsrc

d
) is the smallest number of colors needed to color the edges of G such that any two vertices with distance at most d can be connected by a rainbow geodesic. Thus, the value of d is in the interval 1 < d < diam(G). In this paper, we show the lsrc

d
of prism graphs with d = 2 and d = 3, and the generalized formula of lsrc

d
for any value of d.
Characteristic polynomial and eigenvalues of antiadjacency matrix of directed unicyclic flower vase graph
Authors: Aji Bayu H. , Sugeng Kiki A. , Aminah Siti 
Published: January 2021

Abstract
This research discussed the characteristic polynomial and eigenvalues of antiadjacency matrix of directed unicyclic flower vase graph. The entries of the antiadjacency matrix of a directed graph represent the presence or the absence of a directed arc from one vertex to the others. If A is the adjacency matrix of a graph

G

→

, then the antiadjacency matrix B of graph

G

→

is B = J − A, where J is the square matrix with all entries equal to one. The general form of characteristic polynomial coefficients of the antiadjacency matrix of directed unicyclic flower vase graph can be obtained by calculating the sum of determinants of the antiadjacency matrices of all induced cyclic and acyclic subgraphs, while the eigenvalues were obtained by using polynomial factorization and Horner’s method. This paper gives the characteristic polynomial coefficients and eigenvalues of antiadjacency matrix of directed unicyclic flower vase graph. The characteristic polynomial can be considered as a function that depends on the number of vertices.
Determining the premium of paddy insurance using the extreme value theory method and the operational value at risk approach
Authors: Riaman  , Sukono  , Supian S , Ismail N 
Published: January 2021

Abstract
Paddy farming is a source of livelihood for most rural communities in Indonesia. Indonesia as an agrarian country with a tropical climate, where the sun shines all the time and farmers can grow crops throughout the season. However, changes in air temperature, weather, and annual rainfall which sometimes change uncertainly cause changes in cropping patterns, which are caused by minimal water supplies in the dry season and flooding in the rainy season. This uncertainty will certainly increase the risk of crop failure. In addition to the risk of weather, other disturbances from plant pests and plant pests also cause the risk of crop failure, which results in greater losses to farmers. One way to transfer this risk is through a rice agricultural insurance program. This study aims to calculate the premium price using the Extreme Value Theory (EVT) method with the Operational Value at Risk (OpVaR) approach based on weather, pests and plant diseases. In this study, the data used are weather data Pests and plant diseases disturbance in West Java in 2009-2019. The stages in this research, the first step is to determine the estimated threshold value to obtain extreme data, then estimate the parameters using the likelihood method. Data suitability test with Generalized Pareto Distribution (GPD) was performed using the QQplot test. Risk is determined by the Operational Value at Risk (OpVaR) approach, the results of which are used to calculate the appropriate premium for paddy agricultural insurance.
Centrality measures in transportation networks for Unpad campus route
Authors: Napitupulu H , Carnia E , Anggriani N , Supriatna A. K. 
Published: January 2021

Abstract
Centrality measurement still becomes an interesting research topic recently, including its relation to transportation’s effectiveness and efficiency. A transportation network can be expressed in the form of a graph so that even a level of centrality for each vertex of a complex transportation network can be simply analyzed. There have been various developments/modifications of methods on centrality measures in transportation networks. The offered methods show the different points of view regarding which vertices are most important in the transport network. In this research, the study of some centrality measures in the transportation network is discussed. A numerical experiment of some centrality measures implemented to Universitas Padjadjaran (Unpad) campus route as a network is given. The comparisons are done to explore the performance of each method. The calculation is done using Python software with NetworkX library. The results for Unpad campus route show that some vertices (locations) are more prior than another.
Application of GARCH model in the price inflation of foodstuff in West Java
Authors: Nahar J , Hertini E , Supriatna A K 
Published: January 2021

Abstract
The risk and uncertainty faced by consumers and producers due to fluctuations in food prices in recent years have continued to increase. One of them is the fluctuation in the price of foodstuffs which are basic human needs. The process of increasing prices in general and continuously related to the market mechanism which can be caused by various factors is called inflation. Inflation can be measured by calculating the change in the percentage rate of change in a price index. In this study, the index used is the Consumer Price Index (CPI), which is an index that measures the average price of certain goods purchased by consumers. The food price index tends to have high volatility, this can be seen from the sharp increase and decrease in the price of food commodities in Indonesia. Data that has high volatility will be very risky if you use the basic time series method which has stationary data and costly variance, for that we need a method to deal with data that has non-constant and changing variance, or is called heteroscedasticity. Therefore in this study using the GARCH model application to analyze data on foodstuff price inflation in West Java. The results showed that the best GARCH model for foodstuff price inflation data is the ARCH (1) model, which means that the variance of foodstuff price inflation in period t is determined by a constant (1.565) and the remaining square in the previous period with a proportion of 74.41. %.
Dynamic modelling of covid-19 and the use of “Merah Putih” vaccination and herbal medicine treatment as optimal control strategies in Semarang city Indonesia
Authors: Mahardika D , Tjahjana R H , Sunarsih HJ 
Published: January 2021

Abstract
The Corona virus is a disease that threatens human population on earth in early 2020, the first infection began in China, is thought to be a virus that host in mammals and then able transmits into human body, this present paper will describe dynamic system of Covid-19, analyzing direction of the equilibrium, Disease Free Equilibrium (DFE) and Endemic Equilibrium (EE), which can be done by determining dimensionless number of Basic Reproduction Number (R
0). And then we put vaccine and treatment as control variables to reduce the infected population, we use the vaccinations and treatments recommended by the Indonesian government. Furthermore, we use Pontryagin Minimum Principle to find optimal solution of the control. Optimal control method in this paper is fixed time and fixed end point, means that we are determined the duration of the control and set goal for reaching the final state point. This optimal control will aim to minimize the number of infected population and values (cost) of control measures. Numerical calculations also performed to illustrate the graph.
Comparative study of pitch detection algorithm to detect traditional Balinese music tones with various raw materials
Authors: Brata I P B W , Darmawan I D M B A 
Published: January 2021

Abstract
The characteristics of a tone are formed from the fundamental frequency values that make up the tone. A musical instrument’s tone has different fundamental values in building the timbre of the instrument’s tone. This study compares four PDA (Pitch Detection Algorithm) methods and tries to find the best algorithm for detecting Balinese instruments’ tone with different raw materials, namely leather, metal, and bamboo. The PDA method analyzed was the Autocorrelation, ZCR, HPS, and FFT methods. This study also explores the performance of each PDA (Pitch Detection Algorithm) approach in checking the pitch of traditional Balinese musical instruments and focuses on which of the four PDA (Pitch Detection Algorithm) methods detect Balinese musical instruments by comparing the results of the pitch analysis of each line with the original frequency. This study used 193 tone data consisting of Kendang to represent skin, Gangsa instruments to represent metal, Rindik, and Balinese flutes to represent bamboo material. Based on the test results, the PDA (Pitch Detection Algorithm) method that produces the closest value of the four musical instruments is HPS (Harmonic Product Spectrum) and FFT (Fast Fourier Transform) with an average difference of 4.81 Hz and 4.85 Hz.
Comprehensive survey on convex analysis in robust optimization
Authors: Chaerani D , Rusyaman E , Muslihin K R A 
Published: January 2021

Abstract
This paper presents a comprehensive survey on Convex Analysis (CA) in Robust Optimization (RO). Since RO is a class of continuous optimization problem which involved uncertain parameter thus convex analysis is needed to guarantee that the uncertain set is compact set, i.e., closed and bounded. Furthermore, in RO, to handle the uncertainty, the Robust Counterpart Methodology is employed to guarantee that the Robust Counterpart (RC) of the uncertain optimization problem will be ended up in one of the computationally tractable problems, whether it is a linear optimization, conic quadratic or semidefinite optimization problems. The importance of CA in RO lies in a fact that the robustness can be represented by a convex hull, i.e., the set which is the smallest convex set such that the uncertainty set is included in. This convex hull can replaces the uncertainty set. This can be done since determining the solution feasibility with respect to an uncertainty set is equivalent to taking the constraint left hand side supremum over the uncertainty set. If the uncertainty set can be replaced by a convex hull, this yields that the optimal solution remains the same. Thus, this paper discuss the recent researches, the most cited paper, the top journal and publishers also the bibliometric analysis on the topic of CA in RO.
Implementation of Ordinary Co-Kriging method for prediction of coal quality variable at unobserved locations
Authors: Falah A N , Hamid N , Rusyaman E , Abdullah A S , Ruchjana B N 
Published: January 2021

Abstract
A Co-Kriging method is a method that used to predict the value of the point at unobserved locations by sample points are known to be spatially interconnected by adding other variables that have a correlation with the main variable or can also be used to predict 2 or more variables simultaneously. In this research, the Lagrange Multiplier approach is used to produce the minimum variance of the Co-Kriging estimator. The case study is predicted on coal quality variable, Fixed Carbon as the main variable with Calorific Value as an additional variable. The process of prediction calculation by Co-Kriging method using package GStat on R software which produces a best theoretical model is Gaussian model as input in the prediction calculation at unobserved locations. The calculation result with Lagrange Multiplier approach using R Program is faster, precise and accurate which produces minimum prediction variance for Fixed Carbon and Calorific Value variables.
Homogeneous Poisson process in daily case of covid-19
Authors: Alawiyah M , Johar D A , Ruchjana B N 
Published: January 2021

AbstractSince December 2019, an increasing number of new pneumonia cases have emerged in Wuhan, China. The rise of the spread of diseases caused by the Corona Virus Disease (covid-19) which has been established as a pandemic by WHO on March 12, 2020, gave rise to so much anxiety and speculation from various parties. The case of covid-19 positive patients Daily can be calculated by the homogeneous Poisson process. A Poisson process with a constant rate (λ) is called a homogeneous Poisson process. The average number of positive patients of Covid-19 from January 24, 2020, to April 16, 2020, is still very large. The chances of not having cases of covid-19 positive patients from January 24, 2020 to April 16, 2020 are very small so there will always be covid-19 cases every. Therefore, elements of society and government must consider handling and preventing the Covid-19 case.
Ordinary least square and maximum likelihood estimation of VAR(1) model’s parameters and it’s application on covid-19 in China 2020
Authors: Nalita Y , Rahani R , Tirayo E R , Toharudin T , Ruchjana B N 
Published: January 2021

Abstract
Vector Autoregressive (VAR) is a multivariate time series model for examining objects with two or more variables in which the variables affect each other under the stationarity assumption. This study aims to compare the parameter estimation procedure of VAR(1) model of Ordinary Least Square (OLS) and Maximum Likelihood Estimation (MLE) methods. The comparison is investigated by both theoretical and empirical approaches. This study uses daily data of the number of positive cases and the number of deaths caused by covid-19 in China. Result shows that theoretically, the parameter estimation of OLS and MLE give the same results. Empirically, it is proven that the parameter estimation done by both methods provide the same results either in the presence and absence of intercept. For the presence of intercept, the number of positive cases influenced by both the number of positive cases itself and the number of deaths from the preceding period. Meanwhile, the number of deaths is only explained by the number of deaths in the previous period. For the absence of intercept, there is a significant effect of the number of positive cases from the previous period toward the number of positive cases, but the effect of the number of deaths in the preceding period is not significant. Hence, there is no effect of interaction between the number of positive cases and the number of deaths cases and vice versa.
Geographically weighted logistic regression modeling on stunting cases in Indonesia
Authors: Alam F K , Widyaningsih Y , Nurrohmah S 
Published: January 2021

Abstract
Stunting is a condition of failure to thrive in children as a result of chronic malnutrition, so the child is too short at his/her age. Stunting harms children’s growth and affects the quality of human resources in the future. To reduce the prevalence of stunting in Indonesia, the government determined priority areas for handling stunting cases in Indonesia. This study aims to determine the variables that affect the status of priority areas for handling stunting in Indonesia. The model used in this study is Geographically Weighted Logistic Regression (GWLR) as a development of logistic regression model that considers spatial effect. This study used Maximum Likelihood Estimation (MLE) method to estimate the parameter model. The spatial weighting function used in this study is the Fixed Gaussian and Fixed Bisquare kernel weighting functions. The response and predictor variables in this study contain missing values, so Classification and Regression Tree (CART) method used to handle the missing values. The results showed that the best GWLR model on stunting cases modeling in Indonesia is the GWLR model with Fixed Bisquare kernel weighting function with AIC value of 622.806477 and model classification accuracy of 0.7257.
Review of problem-based learning trends in 2010-2020: A meta-analysis study of the effect of problem-based learning in enhancing mathematical problem-solving skills of Indonesian students
Authors: Suparman  , Juandi D , Tamur M 
Published: January 2021

AbstractThe present study analyzes various inconsistent research findings on the effect of problem-based learning (PBL) in enhancing students’ mathematical problem-solving skills (MPSS) in Indonesia. A meta-analysis of 50 primary studies that conform to the inclusion criteria was conducted to summarize, estimate, and evaluate findings of the effect of PBL by analyzing the heterogeneity of the studies. Heterogeneity analysis was conducted by analyzing the effect of moderator variables, namely the characteristics of sample and publication. The analysis tool used the Comprehensive Meta-Analysis (CMA) application by selecting the Hedge’s equation to determine its effect size. The “One study removed” tool in the CMA application was used to analyze the sensitivity of effect size data, and publication bias was assessed by the funnel plot, fill and trim test, and Rosenthal’s fail-safe N test. The findings of the study showed that the overall implementation of PBL had a larger positive effect significantly compared to conventional learning on the students’ MPSS in Indonesia based on a random effect model. The characteristics of the education level and research area significantly affected the heterogeneity of the effect of PBL on students’ MPSS. Thus, these findings suggest that mathematics teachers and lecturers should choose PBL as one of the best solutions in implementing Mathematics learning in the classroom to enhance MPSS. Furthermore, they should pay attention and consider the education level of students and the area where students learn in implementing PBL in enhancing students’ MPSS.
The effectiveness of the blended learning approach in algorithm and programming courses
Authors: Darmawan I D M B A , Linawati  , Wirastuti N M A E D , Nilakusmawati D P E , Raharja M A 
Published: January 2021

Abstract
The purpose of this research is to increase learning achievement by applying the Blended Learning Approach. The Algorithm and Programming course is a subject that requires more problem-solving practice. Learning is done by applying the Flipped Classroom. In face-to-face activities, students do cooperative learning. They discuss the solution of a given computational problem. Student motivation and engagement were measured using the MUSIC® Model of Academic Motivation. MUSIC® Model measures five components, namely Empowerment, Usefulness, Success, Interest, and Caring. Log activities are used to see the interaction between students and Moodle’s Learning Management System (LMS). Log activities show student contributions to discussion forums, number of hits on LMS, number of learning object accesses, and days to access learning objects. Face-to-face learning with cooperative learning trains the ability to work together in groups. The study showed that the Usefulness component had the highest value, with an average of 80.11, while success had the lowest score with a value of 70.16. The learning experience of each student using LMS was different. Students who actively use LMS have better abilities when learning face-to-face. Research shows there is a link between online learning activities and face-to-face learning on learning achievement.