bluuebunny/crossref_metadata_2025_split huggingface dataset:
Forecasting Non-Stationary Time Series with the Multiscale Autoregressive (MAR) Model Approach Using the Haar Wavelet Filter at the Rupiah Exchange Rate Against the Dollar
Authors: Angreni Puce , Fitriani Rahma , Astutik Suci 
Published: March 2021

Abstract
Time series data is a collection of a phenomenon that occurs based on a fixed or at the same time index. Time series phenomena often exhibit non-stationary behavior. One of the time series analyses for non-stationary data is the Multiscale Autoregressive Model (MAR). The MAR model chosen is a model that meets the assumptions of normality and white noise. The predictors used in MAR modeling are wavelet coefficients and scales which are the result of decomposition using Maximal Overlap Discrete Wavelet Transform (MODWT), MODWT functions to decompose data based on the level of each wavelet filter (family). The wavelet filters used in this study are Haar. In this study, the model generated from the data that was stationary first was more accurate than the data that was not stationary first.
Development of Guided Inquiry-Based Instructional Materials to Improve Students’ Science Process Skills
Authors: Br Sitepu Ayu Sri Menda , Sinulingga Karya , Ginting Eva Marlina 
Published: March 2021

Abstract
This study aims to determine the improvement of students’ science process skills by using guided inquiry-based physics teaching materials. This research is a research development (Research & Development) using the Borg and Gall design. This research was conducted at the Smart Nation Private High School with a sample size of 30 students. This research was conducted until the development stage, namely expert validation. The results of the needs analysis and material analysis show that physics teaching materials are needed by teachers and students to support physics learning activities in schools. The teaching materials developed were temperature and heat teaching materials. The results of the validation of the three validators, namely material expert lecturers and media expert lecturers, show that the quality of teaching materials is in the very good category and can be used in the learning process after a long revision, besides that the students’ responses to teaching materials develop in a positive category. The average result of the validation of teaching materials by material experts was 87.5%, and the average validation of media experts was 86.5% with the very good category.
An overview of e-commerce adoption in Indonesian SMEs
Authors: Hasan Amiruddin , Amrusi  , Musfiana  , Mardhani Martahadi 
Published: March 2021

Abstract
This paper aims to provide an overview of e-commerce adoption in Indonesian Small and Medium Enterprises (SMEs). The data were analyzed descriptively using official data from the publication of E-Commerce Statistics. We found a low level of e-commerce adoption, where most businesses use conventional patterns to sell goods and services. The paper concludes that it is necessary to understand better the barriers to small businesses in implementing e-commerce. To promoting accelerated e-commerce adoption, the national and local governments must support through various policy responses.
Development of Physics Teaching Materials with a Guided Inquiry Model to Improve High School Students’ Critical Thinking Skills
Authors: Sari Simatupang Thesa Irene , Siregar Nurdin , Sinulingga Karya 
Published: March 2021

Abstract
The purpose of this study was to develop a guided inquiry-based teaching material to see an increase in students’ critical thinking skills with this type of Research & Development research. Starting from a preliminary study, analysis of student needs, literature study, and field observation, followed by designing a guided inquiry-based teaching material. The teaching materials developed arranged according to the phases in guided inquiry, then assessed by material expert validators and design experts. Teaching materials are also assessed by school teachers and tested on students. The teaching materials developed are temperature and heat. At the design, the results of the teaching material design were obtained based on the guided inquiry model steps. In the results, the developed teaching materials are valid and suitable for use based on the very good category of assessment by the validator with a score of 89.5% by material experts and 95.20% by design experts; by teachers the percentage is 90%. Teaching materials have also been efficient, seen from the improvement of students’ critical thinking with the N-gain analysis in the medium category. It can be concluded that guided inquiry-based teaching materials are valid, practical and efficient so that they can improve students’ critical thinking skills.
Properties of characteristic polynomial and eigenvalues of antiadjacency matrix of directed unicyclic tadpole graph
Authors: Qomaruzzaman  , Aminah S , Sugeng K A 
Published: March 2021

Abstract
A directed cyclic graph is a directed graph that has at least one directed cycle graph, that is a cycle graph in which all edges are oriented, so that the direction passes through each vertex once, except the end of vertex. The directed unicyclic tadpole graph

T

m
,
n

→

is the graph created by concatenating a cycle

C
m

→

and a path

P
n

→

with an edge from any vertex of

C
m

→

to a pendant of

P
n

→

for integers m ≥ 3 and n ≥ 1. Antiadjacency matrix is a directed graph representation matrix based on whether or not there is a relation between one vertex and the others. This paper gives the general form of coefficients of characteristic polynomial and eigenvalues of antiadjacency matrix of directed unicyclic tadpole graph. To find the general form of coefficients of characteristic polynomial and eigenvalues of antiadjacency matrix of directed unicyclic tadpole graph we need to do the grouping of induced subgraphs into acyclic and cyclic and verify with related theorems. After that, the characteristic polynomial is factorized and the roots are calculatedto find its eigenvalues. The coefficients of the characteristic polynomial consist of three distinct values and the eigenvalues are divided into odd case and even case.
The set chromatic numbers of the middle graph of graphs
Authors: Eugenio G R J , Ruiz M J P , Tolentino M A C 
Published: March 2021

AbstractFor a simple connected graphG, letc:V(G) → ℕ be a vertex coloring ofG,where adjacent vertices may be colored the same. The neighborhood color set of a vertexv, denoted byNC(v), is the set of colors of the neighbors ofv. The coloringcis called aset coloringprovided thatNC(u) ≠NC(v) for every pair of adjacent verticesuandvofG. The minimum number of colors needed for a set coloring ofGis referred to as the setchromatic numberofGand is denoted byχs(G).In this work, the set chromatic number of graphs is studied in relation to the graph operation called middle graph. Our results include the exact set chromatic numbers of the middle graph of cycles, paths, star graphs, double-star graphs, and some trees of height 2. Moreover, we establish the sharpness of some bounds on the set chromatic number of general graphs obtained using this operation. Finally, we develop an algorithm for constructing an optimal set coloring of the middle graph of trees of height 2 under some assumptions.
On the resolving strong domination number of graphs: a new notion
Authors: Dafik  , Slamin  , Agustin Ika Hesti , Retnowardani Dwi Agustin , Kurniawati Elsa Yuli 
Published: March 2021

Abstract
The study of metric dimension of graph G has widely given some results and contribution of graph research of interest, including the domination set theory. The dominating set theory has been quickly growing and there are a lot of natural extension of this study, such as vertex domination, edge domination, total domination, power domination as well as the strong domination. In this study, we initiate to combine the two above concepts, namely metric dimension and strong domination set. Thus we have a resolving strong domination set. We have obtained the resolving strong domination number, denoted by γrst(G), of some graphs.
On local irregularity vertex coloring of comb product on star graphs
Authors: Mursyidah I L , Dafik  , Adawiyah R , Kristiana A I , Agustin Ika Hesti 
Published: March 2021

Abstract
Let G = (V,E) be a graph with vertex set V and edge set E. The graph G is said to be a local irregular vertex coloring if there is a function f is a called a local irregularity vertex coloring if : (i) l : (V (G)) → {1, 2,…,k} as a vertex irregular k-labeling and w : V(G) → N, for every uv ∈ E(G),w(u) = w(v) where w(u) = Σv∈N(u) l(i) and (ii) opt (I) = min{rnax{li; livertex irregular labeling}}. The chromatic number of local irregularity vertex coloring of G denoted by Xlis(G), is the minimum cardinality of the largest label over all such local irregularity vertex coloring. In this paper, we study local irregular vertex coloring of G ⊳∘
Sn
when G is complete bipartite graph (Km,p), ladder graph (Lm), fan graph (Fm), friendship graph (Frm), and cycle graph (Cm).
Two-phase method in affine scaling algorithm for linear programming optimization
Authors: Rochani H S , Wiraningsih E D , Hadi I 
Published: March 2021

Abstract
In this paper, the proposed algorithm approaches the optimum solution with a good feasible direction and proper step length. In this method, the initial solution is made to satisfy the feasibility properties. Therefore, the algorithm reduces the number of iterations required to obtain an optimal solution of a given Linear Programming problem and the iterative algorithm itself can be very useful for development of faster technique for solving linear programming problems.
Hashtag activism and message frames: social network analysis of Instagram during the COVID-19 pandemic outbreak in Indonesia
Authors: Priadana A , Tahalea S P 
Published: March 2021

Abstract
During the Coronavirus pandemic, social media played an essential role in disseminating information online by utilizing various message frames and hashtags. Instagram is a popular social media worldwide that are used to spread various information. This study applied the social network analysis (SNA) approach as a theoretical framework and explored how the relationship between users on the Instagram platform related to Coronavirus outbreaks. Moreover, we also investigate how the relationship between users and their hashtags. SNA techniques were used for visualizing network models using an undirected graph, measuring network attributes, and centrality measures to find the most influential users in the network. A total of 10,403 posts based on #wabahcorona on Instagram from February 28, 2020, to May 18, 2020, were analyzed. Based on the analysis results, hashtags play an important role in this topic. Degree centrality measure as connectivity number shows that only two user accounts can make it into the list’s top ten. When using the Eigenvector centrality measure, there are no users in the top ten. The modularity measure detects 122 distinct communities that show the dense connection of nodes in the networks. Betweenness centrality measure shows that there are six related hashtags to COVID-19 pandemic out of ten hashtags. They are #wabahcorona, #covid19, #corona, #viruscorona, #dirumahaja, and #coronavirus and the four are Islamic related hashtags. The Islamic related hashtags are caused by the date of Ramadhan month.
Application of factor analysis method to support the users acceptance model of ERP systems implementation
Authors: Sardjono W , Sudirwan J , Priatna W , Putra G R 
Published: March 2021

Abstract
An e-Commerce company has been using an Enterprise Resource Planning (ERP) system for several years, but is still constrained in its implementation, this is reflected in the number of issue/change request tickets submitted by users who have not been able to reach ideal conditions. To overcome this problem, we need an appropriate reference model, the ERP system user acceptance model in companies. The study conducted factors that influence the level of acceptance of SAP ERP users in the XYZ group to then determine a model that is able to explain practically the level of ERP system user acceptance, which in turn can produce concrete proposals to increase ERP system user acceptance. Research is quantitative descriptive using factor analysis and regression analysis methods. The research method uses a questionnaire with a total of 107 valid respondents coming from 8 company names under the XYZ group in 6 Southeast Asian countries. The conclusion of the study is that there are 24 indicators and 4 factors that influence user acceptance of the SAP ERP system. These four factors are the low contribution of the ERP system, the quality of ERP systems and data, the development of ERP systems, and also the low quality of ERP system supporters. It is hoped that by optimizing the value of the 4 factors, the XYZ group can increase user acceptance of the SAP ERP system so that the system can provide benefits expected by the company to be competitive advantage.
On the student’s combinatorial thinking skills under the implementation of research based learning in solving resolving independent domination number of graphs
Authors: Mazidah T , Dafik  , Slamin  
Published: March 2021

Abstract
The goal of this paper was evaluated the influence of implementing research based learning on student’s combinatorial thinking skill in solving resolving independent domination number of some special graphs. The study applied mix-method that included methods of qualitative and quantitative. The quantitative method was used for statistical analysis on learning achievment test, and qualitative was implemented in the context of interview and observation. The research subject was students of higher education who were divided into two classes, namely experimental class and control class. The experimental class involved 27 respondents and the control class involved 24 respondents. In the experimental class, learning tools were developed and applied to research based learning method, while research based learning method were used in the control class without learning tools. The outcome of data were analysed by using inferential statistics t-test, and the results of independent sample t-test on pre-test was 0,597 (p > 0,05), thus it was not significant, it means the two classes were homogeneous in term of achievment test. The outcome of post-test in independent t-test shown that the sig (2-tailed) is 0,000 (p < 0,05) , so it was significant. Based on the collected data, it means that implementing of Research Based Learning has a mayor effect on student’s combinatorial thinking skills in solving a resolving independent domination number.
Hypothetical learning trajectory design in development of mathematics learning didactic design in madrasah
Authors: Muin A , Fatma M 
Published: March 2021

Abstract
Mathematics learning for most student is still problem. Meanwhile, mathematics is very important in everyday life. The problem is that students experience difficulties in understanding the concept. These difficulties are called epistemological obstacles. It can be reduced by designing teaching materials in accordance with the students learning obstacle. This research was conducted to identify the students’ learning obstacle and create a hypothetical learning trajectory. The research subjects were 30 mathematics teachers at Madrasah Tsanawiyah and Aliyah in South Tangerang. The method used is Participatory Action Research (PAR). In this PAR, the participants involved were madrasah mathematics teachers, Head of Madrasah Education Section of South Tangerang, Head of Development Aliyah Madrasah , and lecturers from Mathematics Education Department. There are two Focused Group Discussion activities of the PAR. The results showed that students in madrasah still experienced many obstacles in understanding mathematical concepts, especially on the topic of functions, circles, sequences and series, as well as comparison due to limitations in conceptual explanations in the learning process. Based on students’ learning obstacle, material hierarchy, and analysis of previous teaching materials, a didactic design was created in the form of hypothetical learning trajectory (HLT). Henceforth, HLT will be developed into teaching materials.
Relationship of self-regulated learning with student learning outcomes in chemistry study
Authors: Fazriah S , Irwandi D , Fairusi D 
Published: March 2021

Abstract
This study aims to analyze the connection between self-regulated learning and students’ chemistry outcomes by large and by gender. The study used correlational technique with a quantitative methodology. Sampling was done using random sampling technique. The quantity of exploration tests was 408 student respondents comprising of 159 males and 249 females. The data collection technique was carried out by using a questionnaire adapted from the Motivated Strategies for Learning Questioner (MSLQ) and documentation study. Data were analyzed using the Spearman Rank correlation analysis technique. The results was obtained that the correlation coefficient in general was 0.272. Meanwhile, the correlation coefficient value based on gender was 0.248 for male students and 0.284 for female students. This shows that there was a positive relationship between self-regulated learning with student chemistry learning outcomes and female students have a higher self-regulated learning relationship with chemistry learning outcomes than male students.
Implementation of Deep Learning Using Convolutional Neural Network Algorithm for Classification Rose Flower
Authors: Anjani Imania Ayu , Pratiwi Yulinda Rizky , Norfa Bagas Nurhuda S. 
Published: March 2021

Abstract
Flora in Indonesia has about 25% of the species of flowering plant species present in the world. Roses are one type of flowering plants and are usually used as an ornamental plant that has a thorny stem. Roses have more than 150 species. In Indonesia there are several flower gardens that is larger than the others. One of the famous flower garden in Indonesia is located on Malang city, East Java. The flower garden in Malang has several varieties of many roses and has a large production of roses. To help the sales system of roses there, the researchers want to create a program that can classify the type of roses in order to help simplify the system of automatic sales of roses without through manual sorting. So that will accelerate the sale of roses with an automated system. Ordinary people with limited botanical knowledge usually don’t know how to classify the flowers just by looking at them. To classify the flowers properly, it is important to provide enough information, and one of them is the name of it. Convolutional Neural Network (CNN) is one method of deep learning that can be used for image classification process. The CNN design is motivated by the discovery of the visual mechanism, the visual cortex present in the brain. CNN has been widely used in many real-world applications, such as Face Recognition, Image Classification and Recognition, and Object Detection, because this is one of the most efficient method for extracting important features. In this research, the classification accuracy value obtained from the test data is 96.33% using 2-dimension Red Green Blue (RGB) input image, and the size of each image is 32 × 32 pixels that are trained with CNN algorithm and the network structure of four convolution layers and four layers pooling supported by dropout technique.
Analysis The Effect of Website Quality on User Satisfaction with The WebQual 4.0 Method and Importance-Performance Analysis (IPA) (Case Study: SPMB Sebelas Maret University’s Website)
Authors: Utami Indah Sri , Winarno  , Setiadi Haryono 
Published: March 2021

Abstract
The digital era describes the presence of technology where everyone can exchange information so quickly by the internet. For an institution, a website has its own benefits, among others, as a media for promotion, presenting information, and providing online services. This study aims to evaluate and improve website performance by analyzing the quality of the Sebelas Maret University selection of new student admissions (SPMB) website by utilizing a combination of WebQual 4.0 and Importance Performance Analysis (IPA) methods. In its analysis, WebQual method looks at 3 main dimensions: Usability Quality, Information Quality, and Service Interaction Quality. This research, which involved students in UNS, found that the website’s gap analysis still has a negative value on all attributes and there are several attributes that require improvement related to website design, presentation of detailed and up-to-date information and navigation on the website. The results from this study are expected could be used as evaluation for the SPMB website’s development to meet user expectation.
Implementation of Naïve Bayes Classifier-based Machine Learning to Predict and Classify New Students at Matana University
Authors: Barus Simon Prananta 
Published: March 2021

Abstract
Data is growing fast, triggered by the wider use of information technology (IT) by the public or organizations. In line with data growth, data processing is also developing. One of them is data mining. Data mining is very necessary in business to obtain the information that needed to make business strategy such as marketing strategy. At Matana University, the Marketing Department needs to utilize data mining to optimize the achievement of its targets, particularly to predict and classify the prospective student data. Current data mining processing machines already have the high performances with large storage capacities. To improve the performance of data mining processing machines, machine learning is applied. The machine becomes intelligent and able to learn from the provided data. The application of machine learning to predict and classify new students is based on supervised learning by applying the Naïve Bayes Classifier (NBC) algorithm. The data used is the data of prospective students who have registered at Matana University. Machine learning is built, using the Python programming language. The result of the application has an accuracy of 0.73 (73%) and very helpful to the head of marketing in making marketing strategies. In the future, several developments can be done such as using other algorithms, accessed by smartphone, using dashboards in visualization, or adding data attributes such as parental income, religion, hobby, future goal and so on.
Science Learning Of Primary Teachers’ Students; an Analysis Study In Covid-19 Era
Authors: Kelana J B , Wardani D S , Arga H S P , Ruqoyyah S 
Published: March 2021

Abstract
Covid-19 changes face-to-face learning to online, this also applies to science learning in elementary education students. This study aims to: 1) determine the learning outcomes and responses of elementary school students to science learning during the Covid-19 period; 2) to find out the obstacles/difficulties in implementing science learning for elementary school students during the COVID-19 period. This study used a descriptive method with a sample of 33 students. The data collection technique used essay test questions, questionnaires, and interviews. The data that has been obtained will be analyzed qualitatively and described in descriptive form as well as Ms. Excel. The results of data analysis showed 1) the average student learning outcomes was 71.06. The other 16 students scored below the KKM and the remaining 17 students had their scores met the KKM scores; 2) student response, almost all students said that online learning was fun, although there were still many obstacles in its implementation; 3) the obstacles faced include inadequate facilities, limited interaction, student interest in learning, lecturers cannot thoroughly control students who are involved in online learning and learning that takes a long time to make students experience boredom. This shows that the use of science learning for basic education students using online learning still needs to be optimized.