bluuebunny/crossref_metadata_2025_split huggingface dataset:
VECM and Bayesian VECM for Overparameterization Problem
Authors: Hapsari Meilina Retno , Astutik Suci , Soehono Loekito Adi 
Published: March 2021

Abstract
Overparameterization is the amount of data used in the study is less than the number of estimated parameters. Overparameterization problems can cause the forecasting ability to be weak because the model is not suitable. This problem often occurs in complex models such as Vector Error Correction Model (VECM). This study discusses VECM and Bayesian VECM (BVECM), which aims to analyze the relationship between macroeconomic variables in Indonesia. First, estimate parameters of VECM with Maximum Likelihood Estimation. Second, estimate parameters of VECM with a Bayesian approach (BVECM). The variables used in this study are six macroeconomic variables in Indonesia in 2010 quarter 1 to 2019 quarter 4 are GDP, the money supply, exchange rate of rupiah to US dollar, exports, imports and interest rates. The amount of data in this study is less than the number of estimated parameters that causing overparameterization problems. Based on literature, Bayesian method can avoid overparameterization problems which can not be overcome by Maximum Likelihood Estimation. The model obtained from this study is the VECM(3) and BVECM(3). In the VECM analysis, the residuals did not meet the assumptions of diagnostic model. However, diagnostics of BVECM models show that it has been proven that the model is suitable. This conclusion is relevant to the statement that the Bayesian method can solve the problem of overparameterization.
Analysis of Students Critical Thinking Ability using Models Scientific Inquiry
Authors: Ginting Samson , Sinulingga Karya , Tampubolon Togi , Rajagukguk Juniastel 
Published: March 2021

Abstract
This study aims to analyze students critical thinking ability in Static Fluid material. This type of research is a quantitative descriptive study. The research subjects were students of class XI MIPA 1 in Senior High School 1 Kerajaan for the 2020/2021 academic year, totaling 30 students. Data analysis was carried out through a test of critical thinking ability in the form of description questions. The test instrument used was 7 items based on the indicators of Ennis ‘critical thinking ability (1995) which had been validated by expert lecturers. From the analysis of the results of students’ critical thinking ability using a model scientific inquiry In the Static Fluid material the average value was 79.52, and after being converted it was in the good category. Of the 30 students of class XI MIPA 1, 15 students (50%) have very good critical thinking ability; as many as 14 students (46.7%) have good critical thinking ability; and as many as 1 student (3.3%) had enough critical thinking ability. Thus it can be concluded that the use of the scientific inquiry model can improve the critical thinking ability sof class XI MIPA 1 SMAN 1 Kerajaan students.
Android-based physics learning-media apps on circular motion
Authors: Wirjawan JVD , Rombe CM , Herwinarso  , Pratidhina E , Untung GB 
Published: March 2021

Abstract
In recent years, the use of Android smartphones in the Indonesia community has increased very fast. Along the way, its use in the Educational aspect rises accordingly. The increase improved significantly during the period of the COVID-19 pandemic burst. While this fact has brought pain and sorrow for many, we looked at it differently. It was a kind of a blessing in disguise. Besides many inconveniences, it also opens plenty of opportunities. Instead of giving up, we prefer to develop android-based physics learning-media apps which is now needed more than before. The increase of the online portion on the learning processes during the COVID-19 pushed our spirit to complete the development of learning media apps. This apps has been tried out by high school students and has gained positive response from its users.
IoT-based Knowledge Repository Design for Supporting Knowledge Integration within the Marine Information System Study Program
Authors: Fitriasari N S , Anzani L , Widiyanto K , Lukman  , Apriansyah M R , Setiawan M A , Asnawiah L P , Shafa M G 
Published: March 2021

Abstract
Knowledge repository is commonly used to store and manage explicit knowledge from knowledge worker. The development of internet of things (IoT) in Industry 4.0 enables the improvement of quality and quantity of knowledge repository. This study focuses on developing IoT-based knowledge repository as a means to support knowledge integration within The Marine Information System Study Program. The study provides architectural designs of a knowledge repository that consists of 5 knowledge domains of marine information system and the design of IoT-based knowledge repository, both of which are based on reviews on relevant literatures and focus group discussion. The solution offered by the current study allows knowledge integration through Community of Practice as the provider and the user of the knowledge.
Mining Social Media (Twitter) Data for Corporate Image Analysis: A Case Study in the Indonesian Mining Industry
Authors: Fahmi D Y , Hartoyo  , Zulbainarni N 
Published: March 2021

Abstract
PT Freeport Indonesia (PTFI) is the largest multinational mining company in Indonesia which frequently becomes trending topics on social media. Since the continuation of the company’s business operations depends on many stakeholders including the regulators, it is important for the company to listen to public opinion in order to develop a solid public relation strategy to maintain its corporate reputation. The objective of this study is to gather insights from social media as input towards a data-driven public relations strategy development. As a case study, we analysed Twitter conversations mentioning PTFI between 20 to 30 August 2020 during which there was a strike in the company. We performed text mining techniques using Drone Emprit system specifically sentiment analysis, bot analysis, and descriptive analysis to get quantitative measures of the corporate image on social media. The findings suggest several improvement opportunities of the current social media strategy of the company including the lack of engagement from local communities, the absence of specific strategy to handle negative sentiment, and the lack of awareness of social media topics not reported by mainstream media. As the implication of the findings, we propose several recommendations including nurturing engagement from employees and local communities, addressing the most influential tweets, and choosing better time periods to get more engagement.
Effect Stretching and Recovery on Delayed Onset Muscle Soreness (DOMS) After Exercise
Authors: Zulaini  , Harahap N S , Siregar N S , Zulfahri  
Published: March 2021

Abstract
DOMS (Delayed Onset Muscle Soreness) is pain that a person feels within 24-72 hours after doing sports activities, and recovery occurs within 4-6 days. Pain is caused by metabolic waste such as lactic acid in muscles and extracellular fluids, irritating the ends of the sensory fibers. An exercise that is not adequately controlled can cause muscle damage, inflammation, and muscle pain. Recovery should be made after each exercise that aims to eliminate lactic acid in muscles. The study aimed to see the effect of stretching and recovery on DOMS after physical activity. This research method is a quasi-experimental research design using a randomized pre and post-test group design. The subjects in this study were students of the Department of Sport Science, Medan State University, who assessed 16 people. The research subjects were randomly divided into two groups. Group P1, namely the physical exercise group without stretching and recovery; Group P2 in the physical exercise group with stretching and recovery. This research will be conducted at the Physiology Laboratory and Physiology Laboratory, Faculty of Sport Sciences, State University of Medan. The results showed that there was an effect of stretching and recovery on the reduction of DOMS after physical exercise.
The Mapping of Ground Water Salinity Using Imagery Data of Aqua Modis Satellite In Kwanyar Bangkalan Area
Authors: Zainab Siti , Handajani Novie , Wibisana Hendrata 
Published: March 2021

Abstract
Salinity is one of the known parameters by water quality researchers as one of indicator to determine the health of water bodies in an area. Whereas soil salinity is an indicator that shows whether the land is suitable for cultivation of rice fields, ponds or for cultivating other crops, or whether the quality of the soil is not good for planting crops. This study aims to map the distribution of groundwater salinity in the Kwanyar Bangkalan area on Madura Island. Since this area is a fairly sloping coastal area, thus there is possibility that the intrusion of seawater will have a significant impact on the distribution of soil salinity. Given the wide coverage area a method that is able to provide solutions in the form of remote sensing technology is used by utilizing Aqua MODIS satellite imagery in the form of a reflectance value calculated by a remote sensing algorithm of groundwater salinity. The results of the calculation are in the form of a thematic map of soil salinity, which statistically has insignificant distribution, which is include by fairlysmall variancevalue with an alpha alpha value 5%, the conclusion is that the use of satelliteimagery is ableto provide updated information in the field of soil salinitymaping forbcoastel area.
Development Interactive Multimedia Based on Web Elasticity and Hooke Law Topic in High School
Authors: Laia Hervin , Rahmatsyah  , Simanjuntak Mariati P. 
Published: March 2021

Abstract
The purpose of this research is to develop interactive multimedia web-based material of elasticity and Hooke’s law in senior high school. This research is a type of research development (Research & Development). The concept used is the Analysis development, Design, Development, Implement and Evaluation (ADDIE). This research is limited to the development stage, namely expert validation. The results of the media expert validation show that the developed web-based interactive multimedia is valid in the display aspect, very valid in the programming aspect, very valid in the usefulness aspect and valid in the language aspect. The results of the material expert validation show that the developed web-based interactive multimedia is valid in the display aspect, valid in the quality aspect of teaching material, valid in the aspect of content, very valid in the aspect of usefulness and valid in the aspect of language. Web-based interactive multimedia is suitable for senior high school physics learning.
Analysis the components of Science, Technology, Engineering, Art and Mathematics (STEAM) in Senior High School Physics Textbook
Authors: Yuni Syafrida , Sahyar  , Bukit Nurdin 
Published: March 2021

Abstract
The purpose of this research was to analyze the STEAM components in physics textbooks for class XI senior high school including balance and rotation dynamics, material elasticity, static fluids, dynamic fluids, heat, kinetic theory of gas, thermodynamics, mechanical wave characteristics, walking waves and stationary waves. Sound and Light Waves, Optical Devices, and Symptoms of Global Warming. This research is a descriptive qualitative research. The subjects of this research consisted of five book publishers. From the analysis with the STEAM indicator, it is found that 60% contains the science category, 30% contains technology, 30% contains the engineering category, 50% contains the art category, 50% mathematics. The results showed that physics textbooks in circulation generally did not emphasize the STEAM approach.
Development of Hypercontent Based Learning Model for High School Students
Authors: Simbolon R. , Saragih A. H. , Situmorang J. 
Published: March 2021

Abstract
In the era of the Coronavirus Disease 2019 pandemic and the development of information technology affecting student learning styles, notably high school students. Researchers in the field of education are competing to find effective and efficient learning models today. This study intends to answer these challenges in a literature review by offering a new learning model based on hypercontent from the synthesis of the ICARE and Blended Learning models. The stages of this new learning model offer an introduction, connection, learning resources, collaboration, independence, celebration, and assessment. The development of learning tools follows the systematic steps of the Borg and Gall development model, with to propose QR code applications on smartphones.
On the sigma chromatic number of the zero-divisor graphs of the ring of integers modulo n
Authors: Garciano A D , Marcelo R M , Ruiz M J P , Tolentino M A C 
Published: March 2021

Abstract
The zero-divisor graph of a commutative ring R with unity is the graph Γ(R) whose vertex set is the set of nonzero zero divisors of R, where two vertices are adjacent if and only if their product in R is zero. A vertex coloring c : V (G) → ℕ of a non-trivial connected graph G is called a sigma coloring if σ(u) = σ(ν) for any pair of adjacent vertices u and v. Here, σ(χ) denotes the sum of the colors assigned to vertices adjacent to x. The sigma chromatic number of G, denoted by σ(G), is defined as the least number of colors needed to construct a sigma coloring of G. In this paper, we analyze the structure of the zero-divisor graph of rings ℤn, where n = pn1
1 P2
n2 …Pm
nm, where m,ni,n2, …,nm
are positive integers and p1,p2, …,pm
are distinct primes. The analysis is carried out by partitioning the vertex set of such zero-divisor graphs and analyzing the adjacencies, cardinality, and the degree of the vertices in each set of the partition. Using these properties, we determine the sigma chromatic number of these zero-divisor graphs.
On the study of local antimagic vertex coloring of graphs and their operations
Authors: Dafik  , Agustin Ika Hesti , Slamin  , Adawiyah Robiatul , Kurniawati Elsa Yuli 
Published: March 2021

Abstract
Arumugam paper studied in et al [4] has inspired us to study the same thing, namely local antimagic edge labeling of graphs. In this paper, we continue to study this type of coloring of some graphs and its operations. By a local antimagic edge labeling, we mean a bijection f from the edge set of G to the natural number up to the number of edges in G such that for any two adjacent vertices v and v’ have different weight, w(v) = w(v’), where w(v) = Σe∈E(v) f (e), and E(v) is the set of vertices which is incident to v. Furthermore, the vertex weight w(v) is assigned as the color on a vertex of G. The local antimagic chromatic number χ1α (G) is the minimum number of colors taken over all coloring induced by vertex local antimagic edge labeling of G.
Local super anti-magic total face coloring on shackle graphs
Authors: Nisviasari R , Dafik  , Agustin I H , Prihandini R M , Maylisa I N 
Published: March 2021

Abstract
We define graph G as a nontrivial, finite, connected graph which contains vertex set V (G), edge set E(G), and face set F (G). We also define g as bijective function that mapping vertex, edge, and face labeling to natural number which starting from 1 until |V(G)| for vertex label, from |V(G)| + 1 until |V(G)| + |E(G)| for edge label, and the last for face label from |V (G)| + |E(G)| + 1 until |V (G)| + | E (G)| + |F(G)|. If there are different weights in any neighboring two faces f1
and f2
has w(f1) = w(f2) for f1, f2
G F (G), so g is considered a local super anti-magic total face labeling. A proper face coloring from local super anti-magic total face labeling caused by assigns the color of face weights to local super anti-magic total face coloring. The minimum number of colors needed for local super anti-magic total face coloring is called The chromatic number of the local super anti-magic total face coloring. γlatf (G) can be denoted as the chromatic number of the local super anti-magic total face coloring. Encryption keys can possibly be created from the result of local super anti-magic total face coloring that can be used to construct a modified Affine cipher and Cipher Feedback Mode. As a result, we have one the orem for the chromatic number of local super anti-magic total face coloring and two algorithms for establishing super anti-magic total face coloring on shackle graphs in Cipher Feedback Mode.
Detection system of facial patterns with masks in new normal based on the Viola Jones method
Authors: Jauhari A , Anamisa D R , Negara Y D P 
Published: March 2021

Abstract
Covid-19 is something that was never expected, it can turn into an endemic virus in the community. There is a possibility that this virus will not be completely destroyed. This makes the world and Indonesia in an uncomfortable position. Two months with Social Distancing conditions, the Government of Indonesia has been preparing to roll back the sluggish economic wheel as a result of the implementation of Social Distancing. Therefore, the Indonesian people must live in peace with Covid-19 until the discovery of an effective vaccine. This condition is called new normal. This study designed a detection system of facial patterns using masks during the pandemic based on Real-Time Raspberry. The purpose of detecting face patterns by using a mask is to find out if there are masked faces in the image. Although it seems easy to do by humans, it turns out that this detection system is difficult to do without the help of a computer to process facial recognition because there are some difficulties related to location, point of view, light, and occlusion. This research has implemented a detection system using the Viola Jones method. Viola Jones method is a method to get fast, accurate and efficient results in face detection on images. This study using the Viola Jones method to adjust the threshold value, and form the Cascade Classifier in determining the face area in the image. This training can be evaluated the accuracy of the system by modifying the parameter values in the Viola Jones method so that this design can produce the highest accuracy for face images using masks and low accuracy for face images without using masks. From the results of trials with 100 face samples, the accuracy percentage is 90.9% and it takes a relatively short time to detect faces using a mask that is on average 15 seconds per sample tested.
MCGDM for selection of OSN participants using integration AHP and MOORA methods
Authors: Kustiyahningsih Y , Sophan K , Ummah N R , Purnama J 
Published: March 2021

Abstract
The Olympics of Science National (OSN) is one of the government’s efforts to improve quality of education. The many indicators of measurement and decision-making involved in process of selecting prospective OSN participants required a decision support system for selection of prospective participants to make it easier and transparent. Indicators in this assessment are academic grades, skills grades, class rank and absenteeism. The science department, academic grades and skills scores have mathematical, chemical, physical, biological sub-criteria. There are geography and economic majors in social science. The method used in the decision support system is Analytic Hierarchy Process (AHP) Multi Objective Optimization on the Basis of Ratio Analysis (MOORA) integration based on group or Multi Criteria Group Decision Making (MCGDM) with geometric mean aggregation. Based on research that has been done with a CR less than 0.01, the accuracy obtained is for physics 89.7%, biology 92%, mathematics 90%,chemistry 93.7%, geography 93.8%, and economics 86.6%. The highest accuracy is in Geography
Credit risk analysis using support vector machines algorithm
Authors: Putri N H , Fatekurohman M , Tirta I M 
Published: March 2021

Abstract
Credit risk or also known as bad credit risk is defined as the risk that occurs due to the inability of the customer to repay the loan and the interest within a certain period of time. Bad credit can be prevented by selecting proper customers during the loan application process so as not to give losses to the Bank. This research aims to analyze credit risk using machine learning methods. One of the machine learning algorithms that can be used for data classification is Support Vector Machine (SVM). The concept of SVM is to find optimal hyper plane with maximum margin to linearly separate the data set into two classes. The dataset were taken randomly from 2015 to 2018 at Bank XX, as many as 610 data. Dataset was divided into two parts along with percentage of the training data 80% and the testing data 20%. The variables used were gender, plafond, rate, term of time, job, income, face amount, warranty, and loan history as independent variable as well as credit status as dependent variable. The testing of SVM algorithm used linear, polynomial, Radial Basis Function (RBF), and sigmoid kernel obtained confusion matrices with accuracy respectively 0.9262, 0.9508, 0.8934, and 0.8361. Meanwhile, the AUC values were 0.9129, 0.9419, 0.9051, and 0.8285. The SVM model with polynomial kernel is the best model of the four models because it has the highest accuracy and AUC value. Thus, this model can be used to classify prospective customers into good credit or bad credit class with sufficiently high accuracy so as to help banks reduce the risk of bad credit.
The implementation of Blockchain framework in MOOCs to support a freedom of learning in Indonesia
Authors: Febrinanto F G , Dafik  , Nisviasari R 
Published: March 2021

Abstract
A freedom of learning program has been released by the Indonesian Ministry and Culture this year 2020. There are three ways for students to earn their credits, namely take the subject course in face-to-face based class, virtual based class or under Massive Open Online Courses (MOOCs). MOOCs is a model that is developed to help people to learn about certain skills through the online platform, without any limitation in the audience. MOOCs aim to enhance broad collaboration between individuals in creating learning environments that have high scalability and can be accessed by anyone and anywhere. The complexity arises when students undertake a subject course through MOOCs, how to certify the completion of their program in which the certification can be gained easily, and the last how secure the obtained certificate? Blockchain technology can help to improve the quality of MOOCs by providing control of academic records as evidence that someone has completed a learning process on MOOCs. Academic records generated will be stored in one place forever and safely stored in the Blockchain environment. This article will explore how the possible to implement the Blockchain framework in MOOCs to support a freedom of learning in Indonesia.