bluuebunny/crossref_metadata_2025_split huggingface dataset:
The bilateral comparison of length standards for measuring end measures in the range up from 0.5 mm to 100 mm (COOMET.L-S22)
Authors: Kostrikov A , Zadorozhna I , Sikharulidze V 
Published: July 2019

The COOMET Project No 765/UA/18 (The bilateral comparison of length standards for measuring end measures in the range up from 0.5 mm to 100 mm), was organized by TC 1.5 (Length and Angle) of COOMET. This comparison started in December 2018 and finished in February 2019. Participants of the comparisons: the NSC "Institute of Metrology", Kharkov, Ukraine (pilot), and Department of Geometric Measurements Institute of Metrology GEOSTM, Tbilisi, Georgia.
These comparisons are supplementary bilateral. The purpose of the comparisons is to determine the equivalence of the measurement standards being compared.
Comparison participants should have the possibility to measure the end measures of lengths from steel with a nominal size of 1.28 mm; 70 mm; 100 mm by the mechanical method. Whatever measuring instruments are used by the participants of comparisons, they should be traceable to the measurement standard of meter.
For bilateral comparisons it is sufficient to establish a pairwise degree of equivalence, i.e. the difference in results between measurements and the corresponding expanded uncertainty with a coverage factor of 2 and a confidence level of 0.95. Calculations approve that discrepancies between the measurement results of deviations are significantly less than the expanded uncertainty, which confirms a good degree of equivalence of the measuring installations of NSC "Institute of Metrology" of Ukraine and YuLOP "Georgian National Agency for Standards and Metrology" (GEOSTM) Institute of Metrology.
KEY WORDS FOR SEARCH
length, end measures of length, mechanical method, deviation

Main text

To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/.
The final report has been peer-reviewed and approved for publication by the CCL, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
The Utilization of Big Data in Optimizing Tax Incomes at Jakarta Provincial Government
Authors: Wang Gunawan , Andriyan  , Kurnia Sari Rini 
Published: July 2019

Abstract
As the highest tax collection province in Indonesia, the DKI Jakarta province has the objective to promote optimization tax incomes and use. Current IT system is dominated with independent applications that make difficult to monitor and control the data. Jakarta government has taken IT initiative to optimize the potential of regional income and encourage the taxpayer compliance in fulfilling the obligation of payment of local taxes as well as the creation of integration of revenue collection amongst all related units. Jakarta governor has encouraged the use of recent IT technology to support faster data retrieval and effective decision-making process. The article proposes the conceptual SOA framework and supported with web GIS and Big Data application to promote data exchange amongst all units. The use of SOA is expected to deliver reliable services, module reusability, scalability and interoperability. The outcome of the article is expected to be used as a reference for all province in Indonesia in integrating data that spread in all districts/sub-districts and task-forces, and promote better decision making.
Application Development and Testing Based on ISO 9126 Framework
Authors: Wang Gunawan , Bernanda D Y , Andry J F , Nurul Fajar Ahmad , Sfenrianto  
Published: July 2019

Abstract
Software quality testing is one of the stages in SDLC (systems development life cycle). Software or application testing can’t ensure quality free of bugs or errors, but can provide trust and assurance to the application at some level. Software of freight forwarding, from the development, implementation and testing of this application can achieve some desired objectives by the user that is to help transportation services become more effective and efficient, providing convenience in terms of data and information process. With the use of the application compared with the process of recording manually is facilitate the decision makers to be able to monitor transactions and reports in a short time. To design and implement reliable Information Systems (IS) of freight forwarding and avoid bugs or errors, comprehensive testing is required based on the ISO 9126 method, which includes attributes such as aspects of functionality and Maintainability. Testing an application or software is an activity to check if the actual results match the expected results and to ensure that the application is bug-free. IS of freight forwarding services is appropriate and able to become software in the desired by the user consisting of input, process, and output.
Enhancement Clustering Evaluation Result of Davies-Bouldin Index with Determining Initial Centroid of K-Means Algorithm
Authors: Jumadi Dehotman Sitompul Bernad , Salim Sitompul Opim , Sihombing Poltak 
Published: July 2019

Abstract
K-Means is one of the most popular clustering algorithms because it is easy and simple when implemented. However, clustering results from K-Means are very sensitive to the selection of initial centroid. Better clustering results are often obtained after several experiments. In this study, Sum of Squared Error (SSE) was used as an approach to determine initial centroid of K-Means algorithm. If the SSE value is smaller then the data in one cluster will be more homogeneous and certainly give a good cluster result. In this study, Sum of Squared Error (SSE) was used as an approach to determine initial centroid of K-Means algorithm. Testing was performed on 3 datasets and the number of clusters 2, 3 and 4. From the test, the average value of Davies-Bouldin Index (DBI) for 3 datasets was 0.2427, while the Simple determine initial centroid of K-Means algorithm obtained an average DBI value of 0.2805. These results prove that clustering with method of determining initial centroid of K-Means algorithm based on Sum of Squared Error minimum able to improve clustering result and enhance DBI value obtained by simple determine initial centroid of K-Means algorithm.
The Factors Influencing Market Price Of Sago Starch In Meranti Islands By Linear Regression
Authors: Arisandi Diki , Hartati Seri , Murtasidin Bahjatul , Syamsuadi Amir , Trisnawati Liza , Elvitaria Luluk , Azhari Herli Muhammad 
Published: July 2019

Abstract
One of the primary food from Indonesia is sago, and one of the sago producers is the Meranti islands. In addition to processed sago products into foodstuffs, sago products are also sold as sago starch. This study discusses the three factors that influence the market price of sago starch are the number of sago farmers, the area of sago land and annual production. Machine learning approach used is the linear regression. After training data, it can be observed that there are two factors that have a significant influence on the market price of sago starch. The results can be reference material for the industrial and trading offices of Meranti islands in observing the annual sago price so that the farmers and sago entrepreneurs can get the appropriate price of sago starch.
Learning Culture Framework in E-Learning for the Equivalency Education Program (E-LEEP Culture)
Authors: Betty Yel Mesra , Sfenrianto Sfenrianto , Wang Gunawan 
Published: July 2019

Abstract
Understanding learning culture based on learning activities is important for learning success in an e-Learning. As an effort that can be done for this purpose, it is necessary to build a student learning culture based on students activities. The study proposes a Cultural Framework for Learning in an E-Learning. It is called E-LEEP Culture because used in an e-Learning the Equality Education Program (E-LEEP). This framework has five key components, namely: Students, E-LEEP, Learning Activities, Learning Culture, and Digital Contents. Learning culture component in E-LEEP Culture Framework consists of sharing activities, getting information, discussingIndividualistic Learning, Collaborative Learning, Learning Time (learn a little), and Learning Time (learn a lot). Each of the components is expected as a basis for providing learning material that suits the needs of students.
Brain Tumour Image Classification Using Learning Vector Quantization Based Zoning Method
Authors: Fahmi F , Priyulida F , Suherman S 
Published: July 2019

Abstract
Brain tumour identification has been increasingly important area, mainly by using CT scan. Neural network and artificial intelligence methods dominate the processing algorithms; however, new methods are expected to emerge. This paper discusses brain tumour image classification by zoning combination using learning vector quantization (LVQ). The matrix results of the zoning are used as the LVQ inputs. As results from the assessment of the twenty normal and abnormal brain images, identification has been successfully carried out by 80% and 90% subsequently for abnormal and normal brain.
Impact Transport Layer Protocol Performances to the Encrypted Traffics
Authors: Suherman S , Panjaitan Sihar P , Gunanta Ginting Andi 
Published: July 2019

Abstract
Transport layer protocols either reliable or unreliable are prone to packet losses. Data transmitted by these protocols are either encrypted or not. The encrypted or compressed traffics are sensitive to losses. Often packet losses lead to failure in extracting the encrypted messages. This paper evaluates the impact of those packet losses on transport layer protocols to the encrypted traffics. The NS-2 simulator is employed and some encryption algorithms are examined. As results, the percentage of successful decryption on TCP is higher than UDP. The higher the packet loss rates the lower the decryption rates. 3DES is more immune to packet losses than Rijndael and Arcfour. In average, it decrypted the encrypted messages 0.38% higher than Rijndael and 0.12% higher than Arcfour.
Adaptive User Interface of Learning Management Systems for Education 4.0: A Research Perspective
Authors: Bagustari B A , Santoso H B 
Published: July 2019

Abstract
The growth of education is dynamically changing along with emerging technology. Learning management systems (LMS) takes an essential place regarding support its process. By many kinds of improvement aspect within technology, adaptive user interface (AUI) has a significant role to maintain students engagement in learning activities. However, it is very significant to analyze the development of AUI in education 4.0 to understand its significant challenge at this stage. This paper discusses AUI in learning system which has been proposed and implemented by other researchers. We apply a comparative perspective between technology and heutagogical aspect in evaluating their approaches. By delivering this perspective, the paper presents a short review of LMS adaptivity trends and development challenges in the field of learning services for education 4.0.
Vision based Eye Closeness Classification for Driver’s Distraction and Drowsiness Using PERCLOS and Support Vector Machines: Comparative Study between RGB and Grayscale Images
Authors: Hazirah Rodzi Anis , Mohd Zin Zalhan , Ibrahim Norazlin 
Published: July 2019

Abstract
Driver inattention and drowsiness are part causes of road accidents in Malaysia. Based on statistics from the Royal Malaysian Police (2016), deaths from road accidents amount is 7, 512 in 2016 compared to 6, 706 in 2015, which is the highest number of deaths recorded. Hence, an assistant system is needed to monitor driver’s condition like some car manufacturers introduced to their certain models of car. The assistant system is a part of main system known as advanced driver assistance systems (ADAS) are systems developed to enhance vehicle systems for safety and better driving. The system is expected to gather accurate input, be fast in processing data, accurately predict context, and react in real time. Suitable approach is needed to fulfil the system expectation. This paper describes the drowsiness and driver in attention detection and classification using computer vision approach. Our approach aims to classify driver drowsiness and inattention using computer vision. We proposed a technique to classify drowsiness into three different classes of eye state; open, semi close and close. The classification is done by using feature extraction method, percentage of eye closure (PERCLOS) technique and Support Vector Machine (SVM) classifier. We examined and analysed the Grayscale and RGB images using mentioned techniques.
Uplifting Student Project Contribution toward Society Through Multimedia Repository
Authors: Angga N M , Pramono R , Putra T D 
Published: July 2019

Abstract
As a developing country, the application of information technology is uncommon in daily business at many fields in Indonesia. On the other hand, information technology students such as in Computer Science Department Universitas Surabaya had created plenty of projects which had been underexposed. Those projects usually created as an answer for the real public issues and problems, therefore they might be an effective means to address some of the community requirements. This research propose a solution in the means of a digital multimedia repository to boost the contribution of the students towards the development of the society.
Citizen Id Card Detection using Image Processing and Optical Character Recognition
Authors: Satyawan Wira , Octaviano Pratama M , Jannati Rini , Muhammad Gibran , Fajar Bagus , Hamzah Haris , Fikri Rusnandi , Kristian Kevin 
Published: July 2019

Abstract
Since its emergence in 2011, Indonesian Electronic Id-card has been widely used as authentication or citizen identity. Several issues like deep difficulty in detecting id-card field and also difficulty in character recognition data in id-card should be concerned. In this research, we propose a technique detect electronic Id-card using combination of Image Processing and Optical Character Recognition (OCR). The result, we can obtain 98% accuracy of Id-card detection using our image processing techniques and OCR. This research was embedded in website interface which used by automotive company.
Impact three pass protocol modifications to key transmission performance
Authors: Badawi A , Zarlis M , Suherman S 
Published: July 2019

Abstract
Key exchange is important to ensure cryptography works as expected. The three pass protocol (TPP) is the popular key exchange protocol. Modifications have been research interest for security improvement. This paper reports experiments to show modification impact to processing time. As modifications applied to 1, 2 and 3 links, the TPP processing time increases exponentially from 79 ms to 511 ms. The modification increases TPP processing time significantly. But modifications have minor impact to encryption and decryption times.
Feature Selection and Rule Extraction Based on Variable Precision Rough Set
Authors: Kesuma I A , Zarlis M , Nababan E B 
Published: July 2019

Abstract
Main factors in feature selection is dimensionality in data and decision making on partial information handling as precision classification errors. This study will demonstrate the feature selection using the rough set method, especially in handling missing information along with an ambiguous decision system with a precision variable-based approach to finding significant features and extracting the required rules. The experiment was carried out with 12 Dermatology datasets from the UCI Machine Learning Repository consisting of 11 conditional attributes and a decision variable. The experimental results show the results of the dominant conditional feature selection of 45% of the overall existing conditional features, along with more concise rules based on selected features.
Identification of The Tuberculosis (TB) Disease Based on XRay Images Using Probabilistic Neural Network (PNN)
Authors: Andayani U , Rahmat R F , Sylviana Pasi Nani , Siregar B , Syahputra M F , Muchtar M A 
Published: July 2019

Abstract
Tuberculosis is an airborne contagious disease caused by the Bacterium Mycobacterium Tuberculosis which means major threat to global health. If Tuberculosis is not treated promptly and quickly, it will cause the disease to get worse. For that, the treatment should not be done carelessly. Therefore, a system is needed to identify the Tuberculosis diseases to help the doctors as an early stage in diagnosing the disease. In this research, Probabilistic Neural Network (PNN) method was used to identify the presence of Tuberculosis by system to help the doctor to make the decision. The stages before doing an identification such as the image acquisition, pre-processing, and feature extractions using Invariant Moment. This study was conducted using train data of 105 normal X-Ray images and 105 images of pulmonary Tuberculosis X-Rays. For the testing data used of 50 X-Ray images. The results showed that the proposed method was able to identify the Tuberculosis disease with an accuracy of 96%.
Analysis of Satisfaction Level with Servqual method using Artificial Neural Networks
Authors: Daniel Sitanggang Erwin , Tulus  , Benyamin Nasution Benny 
Published: July 2019

Abstract
This research aims to analyze the level of student satisfaction at a college in pattern recognition using an artificial neural network with feedforward backpropagation algorithms. Input on the network consists of 5 variables, namely Tangibles (X1), Reliability (X2), Responsiveness (X3), Assurance (X4) and Empathy (X5) which are the dimensions of the Servqual method. Data processing in the Servqual method will become target data on the network. Data is obtained through multi-item questions given to students. After some training trials, the best configuration architecture consists of 5 neurons in the input layer, one hidden layer with seven neurons and one neuron in the output layer. The activation function used by a Sigmoid Binary that has a range of 0 to 1. This architecture can recognize the pattern well in the 14th iteration with MSE of 0.000192. Data testing results obtained an accuracy rate of 91.07% with an error rate of 8.93%. So that it can be concluded that the Artificial Neural Network with feedforward backpropagation algorithm in the case of analyzing the level of student satisfaction on college services can recognize the pattern well.
Heat Transfer Simulation on Window Glass Using COMSOL Multiphysic
Authors: Tulus  , Marpaung T.J. , Siringoringo Y.B. , Syahputra M.R. , Suriati  
Published: July 2019

Abstract
One physical event related to heat transfer is expansion. Where expansion of a substance is an event of changes in the geometry of an object due to the influence of heat. In this study will be discussed about heat transfer based on expansion on window glass due to the effects of heat and solar radiation based on Stefan-Boltzman law. Heat transfer on the window glass will be simulated with a numerical method, namely the finite element method with the COMSOL Multiphysic 5.2a program. The results of this study will show the maximum heat transfer on a window glass that only has 9 degrees in approximately 2.2 seconds.
Process Optimization to Preserve β-Carotene During Palm Fruit Irradiation
Authors: Salamah S , Sarah M 
Published: July 2019

Abstract
Excluded free fatty acid content, palm oil quality was indicated by the presence of minor constituents in palm oil such as β-carotene. Heating utilizing microwave energy degrades β-carotene. This study carried out process optimization to evaluate significant parameters affected palm oil quality during sterilization by microwave irradiation and to obtain optimum process parameters to preserve β-carotene concentration in palm oil. Central composite design (CCD) and response surface methodology (RSM) were used t. The optimum β-carotene concentration in this study was 404 ppm obtained from microwave sterilization with combination of mass, power and time approximately 117 grams, 669.087 watts and 5 min respectively.
Monitoring temperature and humidity of server room using Lattepanda and ThingSpeak
Authors: Nasution T H , Muchtar M A , Seniman S , Siregar I 
Published: July 2019

Abstract
To keep the server running properly, the temperature and humidity in the server room need to be considered because if the temperature or humidity in the server room is not suitable with standards it will disturb or damage the existing server. For this reason, the condition of the server room must be monitored and the temperature and humidity in the room are maintained. In this work we design a temperature and humidity remote monitoring system and server room using Lattepanda and ThingSpeak to data cloud of monitoring result. The system design process consists of two parts, the first is the design of hardware reading data on the sensor. The second is sending data to ThingSpeak capable to be resuscitated which is can be accessed via internet using a browser. From the results of the test, it can be seen that Lattepanda can be used to monitor temperature and humidity in the server room. The temperature and humidity can be monitored in real time (every 30 seconds) through the channels provided by ThingSpeak.
Bioinformatics analysis of predicted Ganoderma boninense from oil palm (Elaeis guineensis)
Authors: Basyuni M , Purba A , Putri L A P , Hayati R , Chalil D , Syahputra I 
Published: July 2019

Abstract
The current report examines the bioinformatics approaches to analyse 13 predicted Ganodermaboninense genes from Elaeis guineensisJacq. along with predicted the assembly, pattern, potential transit peptide, and subcellular localisation. The length of the genes was varied with the genes examined, from 209 to 222 bp. It is noteworthy the physicochemical heterogeneity properties consistingcomparative molecular weight, theoretical isoelectric point value, the total atomic number, extinction coefficient, instability coefficient, aliphatic index, and general average hydropathicity along with the analysed genes. Based on stability coefficients, 13 G. boninense genes were unstable proteins, mostly stored in the cytoplasm, microbody (peroxisome), and endoplasmic reticulum (membrane). In contrast to this osbervation, a few genes were existed to the plasma membrane. BLAST search showed that 13 sequences of G. boninenses isolates show high similarity (89-99%) to the G. boninense strain NJ3 in the database of NCBI.These findingspointed the significantknowledge on the diversity and role of physical and chemical characteristics of the distinguishable amino acids in G. boninenseisolates.
Analysis of Modified Least Significant Bit Polynomial Function Algorithm For Securing Digital Image
Authors: Rachmawati Dian , Sharif Amer , Adrinta Abdurrazzaq Muhammad 
Published: July 2019

Abstract
Nowadays, there are many types of information, among which is the digital image. Some information must be secured, so it has to be made confidential. One of the methods to secure data is by steganography, wherein information is hidden inside another media called cover. Least Significant Bit (LSB) is the smallest bit in the binary array from the value of a byte. The polynomial function is the total of the power product in one or more variables with coefficients. The digital image can be used as a cover in steganography. The pixel selection for containing the message may be determined by the polynomial function so that the polynomial function can be used as the embedding and extraction key. The larger the ratio between the dimensions of the cover image to the image message, the better values of PSNR and MSE obtained. It can be concluded that the combination of the LSB method and polynomial function may serve as a modification to the LSB method in steganography.