bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bilateral comparison of 1 Ω and 10 kΩ standards (ongoing BIPM key comparisons BIPM.EM-K13.a and 13.b) between the NIM (The People's Republic of China) and the BIPM
Authors: Rolland B , Stock M , Yunfeng L , Jianting Z , Qing H 
Published: July 2019

This report gives the result of a bilateral comparison of resistance between the NIM (The People's Republic of China) and the BIPM carried out at the end of 2018, beginning of 2019. Two 1 Ω and two 10 kΩ travelling standards belonging to the BIPM were used. The comparison was carried out with an 'A-B-A' pattern of measurements; the standards were measured first at the BIPM for a period of about one month, then for a period of one month at the NIM, and finally again at the BIPM. The measurand was the 4 terminal dc resistance at low power. The BIPM was the pilot laboratory, and the comparison forms part of the ongoing BIPM key comparisons BIPM.EM-K13.a (for 1 Ω) and BIPM.EM-K13.b (for 10 kΩ).
The results from the NIM and the BIPM were found to be in good agreement, with a difference smaller than the relative expanded uncertainties (95% confidence, k = 2) for both 1 Ω and 10 kΩ standards. Relative differences are + 0.010 × 10−6 for 1 Ω and − 0.001 × 10−6 for 10 kΩ with a relative expanded uncertainty of 0.034 × 10−6 for 1 Ω and 0.032 × 10−6 for 10 kΩ.
KEY WORDS FOR SEARCH
Resistance; ohm; NIM; The People's Republic of China; BIPM; CIPM MRA; comparison; K13; electricity

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 CCEM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
Face recognition system Using Deep Neural Network with Convolutional Neural Networks
Authors: Fernando Erick , Andwiyan Denny , Fitria Murad Dina , Touriano Derist , Irsan Muhamad 
Published: July 2019

Abstract
Face recognition has long been a hot topic and challenging research point in areas such as image processing, pattern recognition, and machine vision. The face is a biometric feature with the intrinsic nature of a human. So that the face has self-stability, deep individual differences and can be an ideal basis for verification of an identity. In this research use, Deep Learning Network method uses to perform detection or face recognition. In this study, we present a framework that can be used to detect faces. This research is also able to present a DNN model that is used to study data sources from the data stream in sequence. The most important part of this study is able to adjust the capacity of the model from the simple one. This research uses experimental design method. The first step is a collection of face image data. Then the architecture design starts from the determination of the depth of the network, layout layers, and the selection of layer types that will be used to get the model based on input dataset and label name index.
Application of Classification Method C4.5 on Selection of Exemplary Teachers
Authors: Siahaan Hasudungan , Mawengkang Herman , Efendi Syahril , Wanto Anjar , Perdana Windarto Agus 
Published: July 2019

Abstract
The study aims to analyze the selection of exemplary teachers using C4.5 algorithm, which is one of the existing decision tree methods in data mining theory. Teacher data was obtained from the school in SMA Negeri 2 Pematangsiantar (2010-2016). The data used contains information about teacher history and teacher assessment data. This research uses interview technique and questionnaire in obtaining data. There are 11 attributes used in the assessment process: NUPTK, name, age, education, status, Appointment Letter, competence, award, work, teaching load, personality, Position, and label. The system has been tested using the Rapidminer application with 16 data samples. Where the rules are obtained as many as 24 rules. The level of accuracy of the system states that four of the ten attributes have a very significant correlation to the model of relationship rules in determining the proposed model teacher, such as (Position, competence, education, and personality). The four attributes (Position, competence, education, and personality) contribute 82.8% to the model of the rule of connectedness rules in determining the best teacher.
Improving One-Time Pad Algorithm on Shamir’s Three-Pass Protocol Scheme by Using RSA and ElGamal Algorithms
Authors: Purnomo Sidik Agung , Efendi Syahril , Suherman Suherman 
Published: July 2019

Abstract
This study aims to cover the shortcomings of the one-time pad algorithm used in the Shamir’s three-pass protocol scheme. In this study, the technique used to cover the weakness of one-time pad algorithm is by changing each ciphertext generated from the three paths in the three pass protocol scheme. Ciphertext modification is performed by encrypting the cipher-text by using the RSA and Elgamal algorithms to generate super ciphertext. The first line and the third line are encrypted by using the RSA algorithm and the second line is using ElGamal algorithm. Both algorithms are aimed at keeping no secret key exchange which is a major requirement of the three pass protocol scheme. The evaluation results show that the weakness of one-time pad algorithm can be overcome. Although the processing time of three pass protocol increases, but the longer the plaintext character the closer the processing time ratio to one. The research showsThe only way for plaintext to be formed by cryptoanalysis is they must succeed to decrypt the three super ciphertexts back into the three initial ciphertexts first. But it is not easy if RSA and ElGamal algorithms use the big prime number.
A Strategy using Social Media to Increase Students Engagement in E-Learning for the Equivalency Education Program (E-LEEP)
Authors: Betty Yel Mesra , Sfenrianto Sfenrianto , Wang Gunawan , Nurul Fajar Ahmad 
Published: July 2019

Abstract
Social media can be used to support learning activities in non-formal education. The utilization of social media by students can be seen as a strategy to improve the students’ engagement in e-Learning. It is an important goal for the e-Learning of non-formal education. This study aims to propose a strategy using social media to increase students engagement in E-Learning for the Equivalency Education Program (SosMed E-LEEP strategy). This strategy has several key components. These components are students, social media, E-LEEP, and Students Engagement. SosMed E-LEEP Strategy consists of sharing activities, getting information, discussing, and interacting with students and Tutor, and for learning purpose. Each of these strategic activities is expected to improve students engagement, namely: access to learning materials, forum discussion activities, and assignment uploading.
Cultural Aspects Influencing the Application of E-Learning: A Literature Review
Authors: Permatasari I , Sensuse D I , Santoso H B 
Published: July 2019

Abstract
This research was carried out to identify the influence of cultural aspects on the user experience in applying e-Learning in education. The approach applied in this study is limited to the e-Learning assessment system, which focuses on human-computer interactions but ignores the unique characteristic of the users. Culture is one of the influences that shapes the human pattern of thinking in response to action which results in a reaction. Therefore, investigating the users’ characteristic requires a unification in terms of cultural factors and dimensions (aspects) which are the focus of the findings in this literature review. This paper has found 15 cultural dimensions with six of them that are cultural concepts adopted from Hofstede’s theory, while the other nine are non-Hofstede or compiled theories. The other factor brought up by several researchers in the literature study is the socio-economic factor, but to be considered as a supporting factor (external factor) as it indirectly influences the user experience, and it’s the limitation from this literature. In addition to the cultural aspects, the research was also able to construct a framework to measure the usability of e-Learning application based on the user experience.
Vernam Cipher with Complement Method and Optimization Key with Genetic Algorithm
Authors: Rahman Dalimunthe Aulia , Mawengkang Herman , Suwilo Saib , Nazam Ahmad 
Published: July 2019

Abstract
Integrity is important aspect on the process of exchange data, because the originality of the data sent must be kept confidentiality from the irresponsible attacker. One of the algorithm on cryptography is Vernam Cipher which main focus on XOR operation for encryption and decryption process. The key length and the complexity of algorithm for key determination are very influential to avoid attacks. This aim of study is to modify Vernam Cipher with addition 2’s complement operation on encryption, decryption and key optimizing. Modified Vernam cipher generate random key by genetic approach to improve level of security and complexity of the algorithm.
3D anatomy learning system using Virtual Reality and VR Controller
Authors: Fahmi F , Nainggolan F , Siregar B 
Published: July 2019

AbstractAnatomy is the branch of biological science in medical education that focuses on structured parts of living things, especially the human body. This subject is quite difficult to learn especially if only done by reading a book. Technological developments, especially applications based on 3 dimensions, are expected to help the learning process of this science subject. In this study, we proposed the use of virtual reality (VR) with an assigned controller as a tool for studying anatomy. With VR along with the controller, users experienced immersive experience while studying anatomy that they cannot get through learning by reading books only.
Identification of Retinoblastoma Using the Extreme Learning Machine
Authors: Jaya I , Andayani U , Siregar B , Febri T , Arisandi D 
Published: July 2019

Abstract
Retinoblastoma is cancer on the retina that often occurs in infants and children that can cause blindness and even death. The cause of retinoblastoma is due to the mutation of the RB1 gene which keeps retinal cells reproducing until the tumor grows on the retina. In general, to identify a retinoblastoma the doctor uses an ophthalmoscope that shines brightly through the pupil to examine the back of the eye and see the presence of white or yellowish white tumor lesions in the eye. In addition, the examination is also done by analyzing the retinal fundus image from the fundus camera. The image of the fundus camera is re-analyzed by a doctor or expert to determine whether or not there is retinoblastoma. Therefore, a system is needed to help the expert to diagnose retinoblastoma. The method used in this study is the extreme learning machine. Retinal fundus images are used as input images to identify retinoblastoma. Before being identified, pre-processing of the image is carried out, it consists of scaling, green channel, contrast stretching, thresholding, and feature extraction using the zoning method. From this study, it was concluded that the proposed method had the ability to identify retinoblastoma with an accuracy of 92%.
Optimizing Lot Size of Flexible Job Shop Problems by Considering Expiration Aspect
Authors: Suzana Yenny , Mawengkang Herman , Ramli Marwan , Salim Sitompul Opim 
Published: July 2019

Abstract
Production planning for manufacturing companies is an aspect to meet production needs for production process. The production need of fish canning companies is uncertainty aspect and this includes in the flexible job shop system, the issues of uncertainty. The process of fulfilling the needs with consideration of expiration in the fish canning company is to optimize lot size with assumption that customer demand can be met on time without reducing consumer trust. Mathematical formulations used to meet the needs of the FJSS problem use lot-sizing techniques in making decisions. Stochastic programs can be used to obtain the desired formulation. Solution for ordering quantities and the number of quantities ordered plus expiration considerations are formulated with mixed integer linear programing.
The cryptanalysis of the Rabin public key algorithm using the Fermat factorization method
Authors: Budiman M A , Rachmawati D , Utami R 
Published: July 2019

Abstract
As a public key cryptography algorithm, the Rabin algorithm has two keys, i.e., public key (n) and private key (p, q). The security of Rabin algorithm relies on the difficulty of factoring very large numbers, so the greater the private keys are used, the better the security becomes. In order to test how hard it is to cryptanalyze the Rabin public key n, we use the Fermat factorization method to obtain the values of p and q. After obtaining the factors, both of these factors are tested whether or not they are in accordance with the Rabin private key requirements. The first is to test whether or not the factors are prime numbers using Fermat Little Theorem. The second is to test whether or not the factors are congruent to 3 in modulo 4. If the results of the two tests turn out to be positive, then the factors are indeed p and q, the private keys of the Rabin algorithm. The result of our experiment indicates that the value of public key n does not have a directly proportional correlation to the factoring time. A factor which may affect the factoring time is the difference between the private keys (p - q): the larger the difference, the longer the factoring time.
The implementation of RC4+ and Variably Modified Permutation Composition algorithms in the three-pass protocol scheme for data security
Authors: Budiman M A , Rachmawati D , Badegeil R A 
Published: July 2019

Abstract
The science and art that is used to take care of message security by encoding messages into obfuscated forms is called cryptography. In cryptography, there are two types of algorithms, which are symmetric and asymmetric algorithms. The RC4+ algorithm and the Variably Modified Permutation Composition (VMPC) algorithm are examples of symmetric algorithms in the form of stream ciphers where the process of encryption and decryption is done by using the same key. To achieve the security objectives, these two algorithms are then used and applied into the three-pass protocol scheme. The three-pass protocol is a cryptographic scheme for sending and receiving messages that allows one party to securely send messages to a second party without the need to exchange the keys. As a result, this research succeeded in securing text file with (*.docx) dan (*.pdf) and can restore the data back as before by combining the RC4+ algorithm and the Variably Modified Permutation Composition (VMPC) algorithm in the three-pass protocol scheme. The theoretical complexity of these two algorithms is θ(n) both for encryption and decryption. The actual running time is directly proportional to the length of the character of a file.
Identification of Cervical Cancer Cells using Backpropagation
Authors: Fajriani  , Rahmat R F , Purnamawati S 
Published: July 2019

Abstract
Cervical cancer is the growth of abnormal cells in the cervix. In general, cervical cancer can be early detected through Pap smear. This examination aims to see the existence of changes in cell shape from digital microscopic images, but it is still manually performed. Therefore, a method is required to identify the cell of cervical cancer automatically. Under this research, the proposed method consists of three primary processes. The initial stage is image input. The process continues to the pre-processing phase which involves scaling, grey-scaling, median filter and thresholding. The final step is identification process using Backpropagation to determine the normal and abnormal cells of cervical cancer. In this research, the training and testing processes used 40 data and 20 data respectively. According to the conducted test, 18 data were correctly identified as the expected output. The study concluded the proposed method performs well in identifying the cervical cancer cells with an accuracy rate of 90%.
Identification of Retinoblastoma Using Backpropagation Neural Network
Authors: Andayani U , Siregar B , Eka Sandri Widya , Muchtar M A , Syahputra M F , Fahmi F , Nasution T H 
Published: July 2019

Abstract
Retinoblastoma (eye cancer) is an eye disease that is usually suffered by children that attack the thin nerve tissue behind the eyes (the part which is sensitive to light). Retinoblastoma can attack one or both eyes and it is a type of disease that can be caused by a genetic mutation called Retinoblastoma1 (RB1). On manual physical examination using ophthalmoscopy by a doctor or an expert there is a yellowish white / white cancer on the fundus that is often caused by the vascularization. That is why it needs a method that can be done to identify retinoblastoma disease through retinal fundus images automatically. In this research the method used is Backpropagation Neural Network using input of retinal fundus image. The stages which is done to identify retinoblastoma disease are image processing (resize, grey scaling, morphological close operation, and optic disk elimination), feature extraction using Grey Level Co-occurrence Matrix method and then classification using backpropagation neural network. After testing on the system in this research, it was concluded that the method used is able to identify retinoblastoma disease with accuracy 90%.
Fish Species Classification Using Probabilistic Neural Network
Authors: Andayani U , Wijaya Alex , Rahmat R F , Siregar B , Syahputra M F 
Published: July 2019

Abstract
The number of varieties of fish species in the same family causes difficulties in classifying fish species directly. Currently, the process of fish species classification accomplished in the fisheries section uses direct eye observations and knowledge assumption and then compares the existing characteristics with reference books. Therefore, an image processing and neural network approach are needed to classify fish species effectively and efficiently. In this study, there are three fish species classified in the Scombridae family, those are skipjack tuna, tongkol, and tuna with ‘out of water’ conditions. The proposed approach utilizes ROI (Region of Interest) in the form of a fish belly. The combination of GIM (Geometric Invariant Moment) feature extraction, GLCM (Grey Level Co-occurrence Matrix) texture feature extraction, and HSV (Hue Saturation Value) colour feature extraction was used to extract features in the image. For the process of determining the type of fish species, the method used is Probabilistic Neural Network. Based on the results of research on 112 images of data training and 29 images of data testing, an accuracy rate of 89.65% was obtained.
Augmented Reality for Presenting Local Wisdom: Sumatera Utara Traditional House
Authors: Syahputra M F , Aulia R , Sitompul O S , Andayani U , Abdullah D , Sriadhi S , Nanuru R F , Utama M D , Manurung R T , Djanggih H , Mouw E 
Published: July 2019

Abstract
Augmented Reality is a technology that allows users to see the real world, with virtual objects placed on it or combined with the real world. Augmented Reality itself can be applied to various things, including as an educational media. In the field of education, technology can be used a culture introduction to society. One part of Indonesian culture is traditional houses. Traditional house is a building that symbolizes the culture of the local community. In North Sumatra itself, there are several traditional houses that have different forms. The use of Vuforia SDK in the construction of this application can display augmented objects in the form of 3-dimentional objects and also provide information on the house. This application will run on the Android mobile platform to make it easier for users to access it. In addition, users can choose their own objects to be used as markers to make the application use much easier.
Diabetic Retinopathy Identification using Deep Believe Network
Authors: Syahputra M F , Rahmah M , Jaya I , Andayani U , Abdullah D , Sriadhi S , Lalusu E Y , Tongko M , Cahya B D , Fardian N 
Published: July 2019

Abstract
Diabetic retinopathy is an eye disease caused by swelling in blood vessels. If it gets worse the blood vessels will rupture and this is the main factor of blindness. This disease is rarely found in children and symptoms can be seen during puberty. One way to find out this disease is a wide and comprehensive pupil jerky eye examination performed by an ophthalmologist manually. Manual examination takes a long time and can cause misidentification because the similarity of characteristics of diabetic retinopathy is difficult to see directly. Because of this problem a method is needed that can facilitate the eye doctor in identifying diabetic retinopathy by simply inserting a retinal image into the system. The method proposed in this study is Deep Belief Network (DBN). The steps taken before identification are the image of the retina undergoing pre-processing in the form of grayscale, median filter, contrast stretching, morphological close operation and feature extraction using the Grey level Counselling Matrix (GLCM). In this study it was shown that the proposed method was able to identify diabetic retinopathy with 84% accuracy, sensitivity 93%, and specificity 70%.
Forensic in information technology: A redefinition
Authors: Nasution M K M 
Published: July 2019

Abstract
The foundation for the development of theory is the definition. In a scientific culture, definitions force a scientific field to be present. However, the term and meaning always present a different framework for definition. This paper aims to redefine computer forensic science based on the existence of forensic terms and the relationship between these terms. A new definition is completed based on the reciprocal function of this field, a definition related to information technology.
Building the Application to Identify Incorrect Capital Letters Writing in Bahasa Indonesia
Authors: Gunawan D , Amalia A , Maringga O N 
Published: July 2019

Abstract
Ejaan Bahasa Indonesia (EBI) is a set of writing rules in Bahasa Indonesia which is implemented since 2015 according to the government rule Peraturan Kementerian Pendidikan dan Kebudayaan Republik Indonesia Nomor 5 Tahun 2015. This new set of rules replaces previously implemented rules which are known as Ejaan Yang Disempurnakan (EYD). The capital letter rule is one of the elements of EBI. According to the official dictionary of Bahasa Indonesia, the capital letter is a letter which has a bigger size and particular form than the common letter. This research yields an application to identify the incorrect capital letter writing in Bahasa Indonesia based on the user input. The application implements Part of Speech Tagging (POS), Named Entity Recognition (NER), N-Gram and set of rules based on EBI. As the conclusion, the application is able to check 81.57% words that should be written in capital form.
Design of the research problem statement
Authors: Nasution Mahyuddin K M , Onrizal  , Aulia Indra 
Published: July 2019

Abstract
This paper aims to provide an understanding of designing a problem statement that must be present in every research proposal or other scientific work. A study, from proposals to scientific papers, requires a problem statement. The design of the program statement is basically always present from research interests. Objectives as a translation of the problem statement will be described through a methodology that matches the answers to be given to the interests. In the industry 4.0 era, problem statement in research prioritize innovation or change to improve welfare.