bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of problem based learning models with 3D thinking maps on creative thinking abilities and physics learning outcomes in high school
Authors: Bektiarso S , Dewi D R , Subiki  
Published: March 2021

Abstract
The purpose of this study is to examine the effect of Problem Based Learning with 3D thinking maps on the ability to think creatively and physics learning outcomes. This research is a true experimental research design with the Posttest Only Control Design. The data analysis technique used is a statistical test with a different test technique (t-test) using SPSS 23. Experimental class learning using Problem Based Learning accompanied by 3D thinking maps, whereas for the control class do not use it. The normality test results of student learning outcomes in the experimental and control classes are not normal, so the t test on student learning outcomes uses the Mann Whitney U Test. T test results of student learning outcomes that have a Sig (2-tailed) value of 0,000 then the value is below 0.05 which indicates that Ha is accepted (Ho is rejected) then it can be concluded that the Problem Based Learning model with 3D thinking map affects the physics learning outcomes in high school.
Introduction of the integrative STEAM approach as a learning innovation in the COVID-19 pandemic in South Kalimantan
Authors: Pasani C F , Amelia R 
Published: March 2021

Abstract
The COVID-19 pandemic has forced all communities to have technological knowledge, particularly in the education sector. This study aimed to introduce the integrative STEAM approach as a learning innovation in the COVID-19 pandemic for schools in South Kalimantan, Indonesia. The implementation of the 2013 thematic integrative curriculum in elementary schools is a unique challenge for parents in guiding their children. One of the suitable approaches following this demand is integrative STEAM (Science, Technology, Engineering, Arts, and Mathematics). This approach is able to perform creative and innovative learning by utilizing integrated technology in accordance with the 2013 Curriculum in elementary schools. The total of 120 correspondents participated in the service activities aimed to introduce this approach, and it consisted of Elementary School teachers and its students’ aide in the South Kalimantan. This introductory activity began with the presentation of the approach, followed by a discussion session as well as questions and answers, which ends with an evaluation of its implementation by filling a questionnaire. The results showed that 93.75% of the participants were interested in the presented topics since they aroused their curiosity. Therefore, it can be concluded that there is an increase in insight and knowledge about the integrative STEAM approach to the participants.
Model of developing key performance indicator to increase the quality of education during the Covid-19 pandemic
Authors: Selviyanti E , Sardjono W , Mukhlis M , Tohir M , Maswar M , Fariz A 
Published: March 2021

Abstract
Indonesia is one of the countries whose people are most affected by the 2019 corona virus (COVID-19). When the corona virus spreads faster, the Indonesian government imposed large-scale social restrictions in big cities to villages in Indonesia. With the changing situation in carrying out work activities during this pandemic, it will certainly affect the quality of organization in companies and the quality of education in schools and colleges. In order to identify all processes in teaching and learning activities that are running well or not, schools need to monitor and measure employee performance. Key performance indicators (KPIs) are generally used as benchmarks to determine how well a company’s performance can be represented by employee performance. In this study, the key performance indicator preparation process was carried out through the stages of designing a questionnaire, distributing questionnaires to employees in educational institutions, conducting factor analysis and then developing a KPI model. The output is in the form of a KPI model that can be used as a reference in the formation of KPIs in educational institutions, namely Y = 5,360 + 1,380 X1-1, 068 X3.
Blended learning: its effect towards Higher Order Thinking Skills (HOTS)
Authors: Yusuf I , Widyaningsih S W , Prasetyo Z K , Istiyono E 
Published: March 2021

Abstract
This research was aimed at evaluating the HOTS of the students after implementing the blended learning model. This research was a quasi-experimental type of pre-test post-test control group design. The purposive sampling technique was used to determine 2 research samples, namely biology education class as an experimental class taught using blended learning and mathematics education class as a control one. The purposive sampling technique was used to determine 2 research samples. The instrument used in this study was HOTS which consisted of 24 multiple choice items that had met validity and reliability criteria. The data of students’ HOTS was obtained from pre-test and post-test scores. The analysis technique was in the form of gain and effect size test as well as prerequisite test and hypothesis testing. The analysis results showed differences in the experimental class average post-test scores were 66.52 ± SD 17.69 and the control class was 42.01 ± SD 22.55, the experimental class gain score was 0.58 (medium) and the control class was 0.24 (low) and the experimental class effect size was 2.39 (high) and the control class was 0.53 (medium). The result of normality and homogeneity test of HOTS data showed normal and homogeneous results so that it could be proceed with hypothesis testing through t test. The result of the t-test analysis with a significant value (2 tailed) was 0.00 less than 0.05 or there were significant differences. It can be inferred that HOTS taught by students through blended learning is better than conventional models.
Analysis of physics concept in the traditional brown sugar making process
Authors: Sholihah L , Rahmania U G , Rumiati  , Munawaroh F , Handayani R D , Lesmono A D 
Published: March 2021

Abstract
Brown sugar is one of the traditional artificial sweeteners that is widely used by Indonesian people. Unfortunately, society considers that the brown sugar-making process is only a step of unscientific traditions and habits. This research aims to explore the physical concepts of heat transfer in making traditional brown sugar. Data were gathered through interviews, documentation, and observation. Analysis of the data used is descriptive qualitative with triangulation techniques. This research represented that brown sugar manufacturing contains heat transfer processes of conduction, convection, and radiation in the Ndewan processes. The conduction process occurred in the furnace (heat source), which propagates in the pan during the heating process, and the convection process happened when the palm sap is heated. Also, the radiation process transpired around the furnace. This study is expected as alternative teaching material in the learning physics class to be more contextual.
Prospective teacher’s expectation of students’ critical thinking process in solving mathematical problems based on Facione stages
Authors: Tohir M , Maswar M , Mukhlis M , Sardjono W , Selviyanti E 
Published: March 2021

Abstract
The professional teachers have to know about the students’ critical thinking process. So, a teacher can teach mathematics kindly to students at school. Then, all prospective teachers have to like that to be ready to be a good facilitator in the process of learning mathematics at school and others. This study aimed to describe the critical thinking process expected by prospective teachers to students in solving mathematical problems based on critical thinking stages of Facione’s theory. The research method used is descriptive research employing a qualitative approach. The subject of the study was the prospective mathematics teachers who were students of the Mathematics Study Program at Ibrahimy University, Situbondo, Indonesia. The data were collected by giving an essay test item to prospective teachers. The test was given to collect data related to the critical thinking process of prospective mathematics teachers. Moreover, the data collected through observations, tests, and interviews were analyzed and tested for their validity by using triangulation. The data analysis technique used is qualitative descriptive data analysis. The results of this study indicate that: (1) each of group subjects’ expectations tend to have different expectations for students’ critical thinking processes; (2) the high-group subject tend to expect that students follow and complete all of the critical thinking process stages according to Facione’s theory; (3) the moderate and low-group subjects tend not to expect their students to follow and complete all of the critical thinking process stages according to Facione’s theory; and (4) the percentage of indicators achievement of critical thinking processes expected by prospective teachers to students in solving problems based on Facione theory was revealed to be; Identify (57.14%), Define (50%), Enumerate (78.57%), Analyze (50%), List (39.29%), and Self-Correct (32.14%). The results of this study can serve as the fundamental to be discussed within the teacher’s summit in finding out the critical thinking process expected by teachers towards the students, because it will have a positive impact both on themselves and their students.
Analysis of image representation capability in physics learning through the textbook based process image
Authors: Jamilah R N , Mahardika I K , Indrawati  
Published: March 2021

Abstract
Physics is closely related to verbal concepts, pictures, graphics, and mathematics. The results of learning physics can not only be seen through the ability of students to represent physical concepts verbally and mathematically, but can also be seen through the ability to represent in the form of images and graphics. This study aims to analyze the abilities of students in interpreting process images in physics learning in the subject of direct current electricity. This study uses quantitative descriptive research by involving high school/MA grade XII students as research subjects. The analysis in this study was carried out with the analysis of several related journals. The results showed that the level of students’ ability to interpret images in textbooks based on physics learning through physics based textbooks in the process included in the sufficient category.
Uphill running exercise of speed on futsal extracurricular high schools
Authors: Hartati  , Aryanti S , Destriana  , Pangestu E 
Published: March 2021

Abstract
The purpose of this study is to determine the effect of uphill running exercises on the speed of soccer extracurricular participants in senior high school number 6 Palembang. This research is an experimental research design with Quasi Experimental Design in the Nonequivalent Control Group Design. The population in this study is 60 people, and the sample in this study is the same as the total population. The sampling technique in this study uses a systematic sampling technique with ordinal pairing system. The experimental group was the group given treatment in the form of Uphill running while the control group is the group that was not treated. The type of instrument used in this study is the 60meter run test or often called the 60meter sprint test. This form of test is used in the initial test (pre-test) and final test (post-test) which aims to determine the fastest time prediction level of students, the results obtained by the average experimental group time at pre-test of 75 and post-test 79.1, and obtained the average results the average time of the control group at the pre-test was 74.9 and the post-test was 76.4. After testing the results of the data were analyzed using statistical data analysis techniques t test with a significant level (α = 0.05). Based on the data analysis of the research results obtained tcount = 14.33, and ttable = 1.675. The findings in this study are that uphill running exercises significantly influence the speed of soccer extracurricular participants. it can be concluded that the existence of uphill running training can affect the speed of the futsal extracurricular participants.
A predicting method for the health state of the rolling bearing
Authors: Jiang Hongyan , Fang Dianjun 
Published: March 2021

Abstract
As an important component of rotating machinery, the health of rolling bearings is related to the normal operation of the whole machinery. A Period-Sequential Index (PSI) method was used for forecasting the three working states of the rolling bearing: health, fault, or failure. A sample from the vibration signals of the bearing, running only 2538 min because of a fault of its inner race, were tested by using the PSI algorithm. The results show that, this proposed PSI algorithm showed satisfactory forecasting quality in predicting whether the bearing is working in a healthy state or not. And, the value of the mean absolute percentage error at a fault state or a failure state was higher than that at a health state.
Applying value stream mapping in packaging industry: a case study
Authors: Joochim O , Jungthawan S 
Published: March 2021

Abstract
The aim of this paper is to increase the productivity of a packaging manufacturing process by using lean manufacturing technique. The current system of this packaging manufacturing process has been mapped using Value Stream Mapping (VSM) tool. This tool is a lean manufacturing tool, and the wastes in the current system are identified. The case study shows how the VSM tool has been utilized for identifying and decreasing the waste in the manufacturing process resulting of the total cost saving of 3,247,251 Thai Baht (THB) per year.
Modified Vgg Deep Learning Architecture For Covid-19 Classification Using Bio-Medical Images
Authors: ANAND R , SOWMYA V , VIJAYKRISHNAMENON  , GOPALAKRISHNAN E.A. , SOMAN K.P. 
Published: March 2021

AbstractThe world encountered a deadly disease by the beginning of 2020, known as the coronavirus disease (COVID-19). Among the different screening techniques available for COVID-19, chest radiography is an efficient method for disease detection. Whereas other disease detection techniques are time consuming, radiography requires less time to identify abnormalities caused by the disease in the lungs. In this study, one of the standard deep learning architectures, VGGNet, is modified for classifying chest X-ray images under four categories. The planned model uses images of four classes, namely COVID, bacterial, normal, and viral images. The performance matrices of the planned model are compared with five deep learning architectures, namely VGGNet, AlexNET, GoogLeNET, Inception-v4, and DenseNet-201.
Performance Analysis of Dimensionality Reduction using PCA, KPCA and LLE for ECG Signals
Authors: Haris Mita J , Ganesh Babu C , Gowri Shankar M 
Published: March 2021

AbstractMachine Learning is a predominantly developing field in the current scenario due to spontaneous growth in size of data. Dimensionality Reduction is significant step used in machine learning. The Imprecation of dimensionality refers to the difficulty that comes up when working with high dimensional data. The Proposed work developed to reduce the risk of high dimensional data representation in the form of low dimensional data representation. This paper presents the dimensionality reduction practices such as Principal Component Analysis (PCA), Kernel PCA and Locally Linear Embedded (LLE).
Multi-objective economic dispatch of distributed generation using differential evolution algorithm
Authors: Mariakuttikan Arumugababu , Rajaram Mahalakshmi , Ananthan Bhuvanesh , Subramanian Kannan , Pandiyan Murugesan Karuppasamy 
Published: March 2021

Abstract
Economic Dispatch (ED) deals with the allocation of the essential load amid the existing power plants such that the operating cost is reduced. The ED problem is framed as a nonlinear optimization problem with subjected constraints. In this study, a distributed generation (DG) optimization using a multi objective differential evolution (MODE) algorithm is explored. This study aims to find out the minimum fuel cost, environmental pollution penalty cost and minimum system real power loss. MODE algorithm is implemented on 33-bus distribution system (DS) to obtain the ideal real power dispatch of DGs. Four DGs are considered which having two diesel generator, one wind generator and one fuel cell. The result shows the minimized value of Fuel/Emission penalty cost and power loss in the DG units using MODE algorithm when compared with Multi Objective Particle Swarm Optimization (MOPSO) algorithm.
Fake news detection using machine learning and Natural Language Inference (NLI)
Authors: Sabarmathi K R , Gowthami K , Sanjay Kumar S 
Published: March 2021

Abstract
The proliferation of misleading facts in everyday get right of to media retailers such as social media, news through online mode, FM Radio, newspapers, TV channels have found it difficult to select authoritative news outlets, for that reason growing the need for ai technologies capable of offer insights into the accuracy of internet resources. We recognize the computerized identification of false news in online mode in this paper. Our approach to this identification of fake news is in two procedural ways. First, we present two new datasets for the undertaking of fake information identification which covers several domains. The Natural Language Interference (NLI) models are also trained. The data collection, interpretation, and testing process are clarified in depth and present various research analyses at the identity of linguistic variations in false and truthful data. Second, we test and train a set of mastering discoveries to create precise fake news detectors. We shall see the process in fake- news detection.
Visual Speech Recognition using Convolutional Neural Network
Authors: Soundarya B , Krishnaraj R , Mythili S 
Published: March 2021

Abstract
Visual speech Recognition or Lip reading is used for teaching differently abled persons to communicate with others. It has been determining speech by looking at the movement of the lips. There are many practical difficulties in traditional lip-reading recognition systems like complicated image processing, difficult to teach classifiers and recognition processes will take a long time. In our paper, we proposed the use of convolutional neural networks- Hidden Markov model (CNN-HMM) in lip reading. Since CNN will assign importance to an input image, it is easier to see a difference among the images. HMM used to handle the dynamics of the image sequence. First we convert the incoming video into images and these images selected for further operation. HMM provides a highly reliable way of speech recognition.
Selective activation of Forearm muscles for improving Wrist Joint Stability
Authors: Arulkumar A , Babu P 
Published: March 2021

Abstract
The wrist movements has important role in the daily life activities. Flexion, ExtensionandAbduction and Adduction are acceptable movements in the wrist. The Strength training of extensionis necessary for prevention of wrist sprains due to flexion movements because flexionforce is morethan extension Aim of this study was to improve the muscle strength by human resistive trainingand inspecting selective activation of forearm muscles in the above movements. 10 subjects wererecruited for performing maximum Isometric contraction at human resistive training and Flexorcarpiulnaris, Flexor carpi radialis,Extensor carpi radialislongusExtensor carpi ulnarisand abductorpollicislonguswereselected for investigation. Surface electromyography was used to get thecontraction level. Ourresult showed co activation of investigated muscles were less in synergistic thanagonist function (FCU:during Abduction 45%, ECU: during Abduction 37%, FCR:during adduction43%, ECRL: during adduction 29%, APL: during flexion 23%) (P<0.0001).In the APL investigation, there was significant difference observed in the interaction effect (P=0.054, F(3, 9)=140.29,ηp2
=0.205). In the isometric training, biomechanical stability of radio carpal and midcarpal wasimproved due to strengthening of forearm muscles.
RETRACTED: Sentimental analysis using Machine learning techniques on python
Authors: Sampoornam K P , Hemalatha B , Kaaviyasri M , Jaya Priyanka K 
Published: March 2021

Abstract
Really, a sentiment alludes to the mirrored image of feelings of people. The modern-day globe seems concerning the strings of feelings. People pleasure this is specific trouble, love, contempt and so on thru precise activities. Division of feelings i.e. good, terrible and nonpartisan, is called emotional analysis. The goal this is essential to research how textual content exam techniques may be nicely used to dive right into a percent of the supplied facts in a improvement of posts zeroing in on diverse styles of tweets dialects, tweets volumes on twitter. The project this is complete finished the use of Python.
A Novel Method of Billing System Using Deep Learning
Authors: Haritha J , Prakash K , Navina B , Saveetha S 
Published: March 2021

Abstract
In order to make the billing process of goods easier and quicker for the customers as well as the shopkeepers, the RFID tags and the bar-codes are used in most of the products. But for the edible products like fruits and vegetables, these tags cannot be used as each item has to be stuck with the tag and its weight must be measured individually. To overcome this, a system is designed in which the weighing and billing of the fruits and vegetables are automated. The proposed billing system consists of Raspberry pi, a microprocessor with a camera module and a load cell. Using Raspberry pi 3 camera module, images of fruits and vegetables are captured and are recognized by using the deep learning technique, ImageNet which is built on Convolutional Neural Network (CNN) architecture and a machine learning technique, K-means clustering is used for classifying the products into corresponding groups. The camera module captures the images of the fruits and vegetables placed on the tray under which the load cell is placed for the weighing purpose. The price of various items per kg is given as an input to the microprocessor. As a result, the Raspberry pi computes the total cost of the items and displays it on the monitor. The general-purpose high-level programming language, Python is used for developing the efficient deep learning algorithm.
Desıgn of Dual Feed Antenna for ultra Wıde Band Applıcatıons
Authors: Priyadharsini S. , Nataraj B. 
Published: March 2021

Abstract
In this study, a simple architecture of UWB antenna with microstrip patch operating in a frequency range of 3.1 to 11 GHz with dual feed structure is proposed. The compactness and low profile of the designed antenna has gained its importance in commercial and industry oriented applications. The proposed antenna radiates well with good return loss, radiation pattern and gain. The results have been obtained by simulating and testing the proposed antenna. The proposed antenna uses FR4 as substrate. The antenna is simulated using HFSS 13.