bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-sensor data fusion algorithm based on the improved weighting factor
Authors: Yu Yongjin , Liu Xiaoqing , Xu Chuannuo , Cheng Xuezhen 
Published: February 2021

Abstract
Aiming at the decrease of the accuracy of fusion data caused by the abnormal value and noise interference in the multi-sensor observations, this paper proposes a multi-sensor data fusion algorithm based on improved weighting factors. Firstly, the Dixon criterion is used to eliminate outliers in observations to avoid data containing gross errors. Then the Kalman filter algorithm is used to effectively reduce the noise impact caused by various reasons and provides the optimal data for weighted data fusion. Finally, an improved weighted fusion algorithm is used to comprehensively consider the nature of the sensor and the influence of various factors in the measurement process to obtain the best fusion data. The simulation analysis of the soil humidity in the greenhouse shows that the error of the multi-sensor data fusion algorithm based on the improved weighting factor is maintained at 0.04%-0.18%. Compared with the adaptive weighted fusion algorithm, the error of this algorithm is reduced by 0.12%, which verifies the algorithm’s effectiveness.
Predictive torque control of SMPMSM drive system based on extended control set and double gradient descent method
Authors: Wang Qian , Li Hongmei , Yang Liguo , Wang Xianling , Ye Wanjia 
Published: February 2021

Abstract
Model predictive torque control (MPTC) has become an effective control method for the permanent magnet synchronous machine (PMSM) drive system in recent years. However, large torque and flux ripples due to the limited numbers of inverter voltage vector deteriorate the steady-state performance. In this paper, a novel model predictive torque control based on extended control set (ECS-MPTC) is proposed. First, an innovative extended control set is generated by the proposed partition method of quasi longitude and latitude lines, in which, many virtual voltage vectors are generated. Then, based on the characteristic of cost function without weighting factor, the optimal inverter voltage vector can be selected quickly by using the double gradient descent methods, and the invalid enumeration can be avoided. Thus, the computation burden can be kept in a low level. Finally, the simulation results of conventional MPTC and proposed ECS-MPTC validate that the proposed control can achieve excellent steady-state performance of PMSM drive system and low computation burden simultaneously.
Research on automatic detection system of encoder accuracy based on PID algorithm
Authors: Hou Han , Cao Guohua , Ding Hongchang , Zhao Changfu , Wang Aijia 
Published: February 2021

Abstract
After the encoder completes the installation and adjustment work, its accuracy needs to be checked again to confirm whether it meets the acceptance conditions. This process is usually manually operated by inspectors, and the inspection efficiency is low and there are certain manual errors. In order to improve this situation, an encoder automatic precision inspection system based on PID algorithm is designed. In this article, the working principle and structure of the detection platform are introduced in the first part, and then designs the corresponding detection software and operation interface according to its working characteristics. Finally, the platform was tested in combination with the actual detection products, and the encoder signal acquisition results were given, which further verified the accuracy and reliability of the detection device. The results showed that the accuracy detection platform can accurately and conveniently realize the error detection of the encoder’s function, and to a certain extent overcome the detection error caused by the drift of the photoelectric autocollimator during the detection process.
K-modes Algorithm Based on Rough Set and Information Entropy
Authors: Xingyu Gong , Ke Cao , Pengtao Jia , Shangfu Gong 
Published: February 2021

Abstract
The traditional K-modes algorithm is susceptible to interference of redundant attributes, and only adopts the 0-1 matching method to define the distance between attribute values of each two objects, without fully considering the influence of each classify attribute on clustering result. In order to overcome these shortcomings, this paper proposes improved K-modes clustering algorithm based on rough set and information entropy. Aiming at a large number of redundant attributes in the clustering data, this paper firstly utilizes attribute reduction algorithm of rough set to eliminate redundant attributes and determine the importance of each attribute, then combines information gain to determine the weight of each attribute and finally makes performance tests of the traditional algorithm and the improved algorithm on five data sets of UCI machine learning library, such as Soybean-Small and Zoo. The experimental results show that the clustering efficiency and accuracy of improved algorithm is higher than that of traditional algorithm, and the performance of improved algorithm is better.
Identifications of Polyphenols and α-Amylase Inhibitory Activity of Multi herbal Formulation: Cocoa Beans (Theobroma cocoa), Buni (Antidesma bunius L. Spreng) and Cinnamons (Cinnamomum cassia)
Authors: Yusuf Muhammad , Pirman  , Nur Fitriani UA , Amri Ibrahim , Juwita A Ita 
Published: February 2021

Abstract
Chemical compounds from cocoa, buni, and cinnamons are expected to inhibit the activity of the enzyme α-amylase, α-glucosidase, and proanthocyanidin as mimetic insulin. Cinnamic acid may inhibit the enzyme activity of HMG-CoA reductase, so that provides benefits for people with diabetes mellitus because it can stimulate pancreatic cells to produce insulin. The objective of this study was to evaluate polyphenols and a-amylase inhibitory activity of a multiherbal formulation. The multiherbal extract prepares with aqueous, acetone, and ethanol. Total phenolic content was found to be 236.28 mg of GAE/100 g (cacao fat extract), 217.94 mg of GAE/100 g (cacao free fat extract), 159.61 mg of GAE/100 g (cinnamons extract), and 181 mg of GAE/100 g (buni extract). α-amylase inhibitory activity found to be 88.74 ppm (cacao extract), 85.32 ppm (cinnamons extract), 83,49 ppm (buni extract), and 13.07 ppm (acarbose). All compounds revealed inhibition potential with IC50 when compared to the standard acarbose.
Augmented reality application: What are the constraints and perceptions of the students during the covid 19 pendemic’s 3D geometry learning process?
Authors: Sudirman  , Yaniawati Poppy , Mellawaty  , Indrawan Rully 
Published: February 2021

Abstract
The Covid 19 epidemic has altered the interplay of the classroom learning process. To facilitate the learning process of 3D geometry, secondary school teachers adopt several technology items. Augmented reality technology is one of those technological goods. This study therefore aims to explain the constraints and perceptions of secondary school students during the COVID-19 pandemic, during the 3D geometry learning process. This study used a qualitative research design descriptive of it. The number of participants to this study was five, namely 3 male students and two female students. Techniques for collecting data using sheets of observations and interviews. Although data analysis by Miles and Huberman [1] adopts data analysis, which consists of data selection, data reduction, data presentation and conclusions or verification processes. Study results show that there are still many challenges faced during the learning process using augmented reality technologies, namely: (a) Constraints when downloading the program on the cellphones of the instructor and the pupil. (b) Marker constraints pertaining to AR identification. (c) Constraints on the student’s smartphone requirements. (d) Limit and network restrictions for accessing the Resources section. (e) Students found too many constraints on appraisal questions on the test checklist. While several challenges do remain, the majority of the students have a good understanding of the learning experience using augmented reality technologies.
Fountains Height Measurement Accuracy With Mamdani Fuzzy Inference System Algorithm
Authors: Devita Retno , Zain Ruri Hartika , Ipriadi  
Published: February 2021

Abstract
Fountains can be found in gardens or offices. The fountain has several patterns for each activation. The pattern height produced by the fountain greatly affects the beauty of a garden. The purpose of this research is to measure the height of the fountain accurately using the Mamdani Fuzzy Inference System (FIS) method. The input of this research is voltage and volume with the output in the form of the height of the fountain. The output produced in the research is a prototype. The results obtained in this study are in accordance with the tests carried out in the field with three tests with the results of defuzzification or confirmation. The height level of the fountains with a value of 34.6 for a voltage of 10 V and a volume of 20 is included in the MEDIUM category.
Decision Support System Using Fuzzy Logic Method of Tahani Model for Student Selection
Authors: Rizaldi  , Anggraeni Dewi , Syah Arridha Zikra , Kholiq Abdul , Agus Raja Tama Andri 
Published: February 2021

Abstract
Tahani model of fuzzy database is one of the methods used for the making decision process. On this occasion, the researcher used the fuzzy database tahani model to build a DSS for the selection of new candidate students at the SMP Taman Siswa Kisaran. SMP is junior high school. This system was built to recommend to principals about new candidate students who are eligible to be accepted. Some of the main variables that form the basis of calculation, namely the average elementary school diploma, including Mathematic score, Indonesian Language score, and Pancasila Education score. The Other variables are Academic Test score and Religious Education Test score. The result of the system recommendations is based on the value of membership and fire strength from the calculation process in the system. To ensure the feasibility of the system, testing the result of the system calculations and comparing them with the results of calculations manually. If the result of the system calculation is the same as the result of the manual calculation, then the decision support system for the selection of new candidate students is feasible to be applied at the SMP Taman Siswa Kisaran.
Analysis of Data Mining in the Group of Water Pollution Areas using the K-Means Method in Indonesia
Authors: Jatnika Hendra , Huda Miftahul , Amelia Ria Rizki , Manuhutu Melda Agnes , Windarto Agus Perdana , Sumantrie Pipin , Waluyo Ari 
Published: February 2021

AbstractWater is an essential requirement in human life. However, pollution causes the water quality to become poor, making it unsuitable for use. Pollution comes from rubbish and waste dumped into rivers, lakes and other water areas. This study aims to carry out a model for mapping areas contaminated with water pollution using artificial intelligence techniques. The data sample comes from the Indonesian Central Statistics Agency (abbreviated as BPS) which consists of 34 records. The data used are provinces in Indonesia that are polluted by water pollution in rural areas. The intelligence technique used is data mining using the k-means method. The variable used is the number of polluted villages by province. The mapping label used is the high cluster (K1) for water pollution and the low cluster (K2) for water pollution. Analysis using Rapid Miner software. The results showed that 4 provinces were included in the high cluster (K1) category, namely North Sumatra, West Java, Central Java, East Java. Testing of cluster results was carried out using Davies Bouldin (k = 2) with a value of 0.328, which means that the cluster results created were optimal. The results of the analysis are expected to be input for the government in focusing on areas polluted with water pollution.
QoS Analysis on Campus Building Network Infrastructure with WDS Technique using PCQ Method
Authors: Ramady Givy Devira , Rahmatullah Griffani Megiyanto , Manullang Martin Clinton Tosima , Zulkarnain Andry Fajar , Sufyani Rosyidin , Hidayat Rahmad 
Published: February 2021

Abstract
The use of internet facilities to support mobility needs in the campus environment such as browsing, downloading and uploading data is an unavoidable condition. Implementation of bandwidth management on campus networks which acts as a bandwidth divider so that it is evenly distributed by adapting the PCQ method to the proxy router device and Wireless Distribution System (WDS) technique so that the signal coverage becomes wider. Analysis conducted on Quality of Service (QoS) in the form of measurements of the quality of internet bandwidth through testing parameters download, upload, throughput, delay, jitter, and packet loss. The test was conducted at the hotspot which is located at several points of the STTM campus social facilities. Based on test results, obtained data before the application of the PCQ method in the form of throughput of 32.76%, jitter of 94.36 ms, delay of 46.83 ms, and packet loss of 20.74%. After the PCQ method is applied there is a change in the results of the parameter test value, the throughput is 41.53%, jitter is 52.48 ms, the delay is 33.62 ms, and the packet loss is 12.57%.
COVID-19 Cases and Deaths in Southeast Asia Clustering using K-Means Algorithm
Authors: Hutagalung Juniar , Ginantra Ni Luh Wiwik Sri Rahayu , Bhawika Gita Widi , Parwita Wayan Gede Suka , Wanto Anjar , Panjaitan Pawer Darasa 
Published: February 2021

Abstract
Covid-19 is an infectious illness caused by a newly identified form of coronavirus. This is a new virus and illness that was previously unknown before the December 2019 outbreak in Wuhan, China. The number of confirmed cases of Covid-19 and the number of deaths due to this virus in Southeast Asia are increasing and quite alarming. Therefore this study will discuss the grouping of Cases and Deaths of COVID-19 in Southeast Asia. The method used is the K-Means Clustering Data Mining. By using this method the data that has been obtained can be grouped into several clusters, where K-Means Clustering Process is applied using RapidMiner tools. Data used are Country statistics, Area of recorded laboratory-confirmed cases of COVID-19, and April 2020 deaths from WHO (World Health Organization). Data is divided into 3 clusters: high (C1), medium (C2) and low (C3). The results obtained are that there are four countries with a high level cluster (C1), one country with a moderate level cluster (C2), and 6 countries with a low level cluster (C3). This can be an input for each country to increase awareness of the transmission of Covid-19.
Sieve Diagram For Data Exploration of Instagram Usage Habit Obtained From Indonesia Questioner’s Sample
Authors: Hidayatullah Reko Syarif , Cholifah Wahyu Nur , Ambarsari Erlin Windia , Kustian Nunu , Julaeha Siti 
Published: February 2021

Abstract
Exploration data using a scatter plot made it more accessible when the datasets correlated. However, the case of Instagram Usage Habit in the previous study was hard to follow. The problem was that many datasets were not specific. Therefore, it difficult to classification for a Decision Tree. The other option of exploration data used the sieve diagram. The sieve diagram summarizes the relationship between the categorical variables using frequencies—the purpose of this study to understand the data and found out what wrong in the datasets. Based on the result of the sieve diagram in the study, the main problem found out in the age of the respondent on attributes. We deduce that several attributes had not characteristic unique for the habit of using Instagram because the attributes based on age have a similar pattern. We suggest that the questions for respondents need to be improved, such as Tiered questions. Therefore, The classification of decision trees would become more precise in the subsequent studies.
Implementation of TOPSIS Algorithm for Selection of Prominent Student Class
Authors: Siregar Victor Marudut Mulia , Sonang Sahat , Purba Arifin Tua , Sugara Heru , Siagian Nancy Florida 
Published: February 2021

Abstract
This study aims to provide the right solution in overcoming the problem of selection for prominent class students senior high school at SMAN 2 Pematangsiantar. The solution is to make a decision support system for the selection of prominent class XI IPA students in determining rankings. The method used is the TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) algorithm by using several criteria, namely: Mid Test Score, Final Exam Score, Extracurricular, Personality, and Attitude. The results of student data processing using the decision support system obtained weights of 1, 0.57188272655161, and 0.56259472567445 for rank 1 to rank 3. The implementation of this Decision Support System is beneficial and makes it easier for the school and the homeroom teacher to determine ranking for the selection of prominent class students.
Evaluating the effectiveness of information security based on the calculation of information entropy
Authors: Imanbayeva Akmaral , Tursynbek Yerlan , Syzdykova Rabiga , Mukhamedova Aigerim 
Published: February 2021

Abstract
Recently, the emergence and increasingly widespread of wireless networks has generated considerable interest in the information-theoretical approach to ensuring secure communications. The basic principle of information-theoretic security requires a combination of cryptographic methods with channel coding techniques that use the randomness of communication channels to ensure that messages sent cannot be intercepted or decrypted by a third party maliciously eavesdropping on the wireless medium. This paper discusses the information-entropy method for assessing security. We show that information-theoretical security means that any algorithm has a negligible probability of violating the security property. This is the same as unconditional security: it does not rely on any computational assumptions and is not limited to probabilistic violators.
Web-Based Online Study Plan Card Application Design
Authors: Lestari Ninik Sri , Ramadi Givy Devira , Mahardika Andrew Ghea , Herawati  , Herlina  
Published: February 2021

Abstract
Filling in the Study Plan Card (KRS) is a part that plays an important role in the academic system. The KRS filling system that has been running so far is still using the manual system. The development of a web-based online KRS application aims to replace the manual KRS system that is running so that later lecture activities can run smoothly. The system development method used is WebE, the system design method uses UML (unified modeling language), and the system test uses a black box system. This application is made with the programming language PHP and MySQL as a database. The results of this study indicate that the application of web-based online KRS applications can make it easier for students to fill in KRS compared to manual filling. This application can also assist the campus in managing data on the number of students who are active in the current semester. However, it is necessary to develop the system that has been made to become a better and perfect system, such as adding the KRS menu for short semesters so that this system makes it easier for students.
Floor Cleaning Robot Control System with Android Based Voice Command
Authors: Dalimunthe Ruri Ashari , Sena Maulana Dwi , Ramdhan William 
Published: February 2021

Abstract
To clean the floor, it can be done manually by using a floor mop along with floor cleaning fluid, but this will result in a floor that is already clean but the implementation time is long enough to interfere with the time of mothers who are office workers or manufacturers to help their husband’s income. . In the process of cleaning the floor, cleaning the floor can be done until the floor is clean so that the children are comfortable playing on the floor. The process of cleaning floors can be done in various ways, either manually or automatically. To clean the floor with a large floor size more quickly, the floor is cleaned with machine power. But the range and limitations of floor cleaning machines exist. So it is necessary to make a robot that works automatically without human assistance to do the cleaning so that the job is done quickly and the area limit of the cleaning results is greater. The system will work using pengerak technology remotely using bluetooth. This system aims to connect communication between wheeled robots and smartphones via Bluetooth communication media. From the test results, the author has successfully applied bluetooth technology to a wheeled robot by providing instructions such as forward, backward, turn right, turn left, and stop. This robot is used to clean floors quickly and practically so that it can be done by itself.
Venn Versus Relation Diagram Models For Database Relation in SQL Command Line
Authors: Kustian Nunu , Julaeha Siti , Parulian Dudi , Selvia Noni , Ambarsari Erlin Windia 
Published: February 2021

Abstract
The study was to analyze the difference between two diagrams, such as a Venn and relation diagram. Comparisons are made based on syntax in SQL Command-Line, primarily when used the Select condition clause. The sample command used for diagrams was inner join and where syntaxes. The diagrams will act as data representation for the Relational Database to display an outline of data relationship analysis. The results obtained that difference between them was significant. The Venn diagram was useful to evaluate how the attribute in the table is connected. The opposite, the relationship diagram, shown how the dataset was related to the tables. Therefore it recognizes the data that had to deceive. However, the more data related then, the more diagram is complex.
Developing Smart Campus Readiness Instrument Based on Pagliaro’s Smart Campus Model and Smart City Council’s Readiness Framework
Authors: Hidayat Wisnu , Hendayun Mokhamad , Sastrosubroto Ashwin Sasongko , Hidayat Rahmad , Haris Samun 
Published: February 2021

Abstract
Smart Campus can be defined as a concept that uses technology in campus life that consists of complex system interactions to support its’s user primary needs, push to achieve higher skill, and motivate problem-solving. Many campuses failed in an attempt to implement a smart campus because of unreadiness in the transformation to be a smart campus. To assess smart campus readiness, assessment is needed using the instrument of smart campus readiness model which evaluate supporting instrument of several aspects which is people and living, economy, energy, environment, and mobility. This smart campus readiness model is developed by combining the smart campus model of Pagliaro and the smart city readiness framework from the smart city council. A smart campus readiness instrument is developed to assess the supporting factor of smart campus indicator in people and living aspect. People and living is an aspect that is directly involved by the improvement of people’s living quality as the user of a smart campus. The instrument is tested for validity to make sure it is used correctly to assess smart campus readiness. The instrument is tested for reliability so it can be used as an assessment instrument of smart campus readiness in another place.