bluuebunny/crossref_metadata_2025_split huggingface dataset:
Indonesian Ethnicity Recognition Based on Face Image Using Gray Level Co-occurrence Matrix and Color Histogram
Authors: Putriany Dinda Mareta , Rachmawati Ema , Sthevanie Febryanti 
Published: March 2021

Abstract
Facial and ethnic recognition became a popular research topic. Different from face recognition, ethnic recognition classifies faces according to the general features of certain ethnic groups. Ethnic recognition in face image is increasingly becoming a necessity and is used in various fields. This paper proposed the Indonesian ethnic recognition system based on periorbital features on facial images. We use the five largest ethnic groups in Indonesia in this study, namely Banjar, Bugis, Javanese, Malay, and Sundanese. Gray Level Co-occurrence Matrix and Color Histogram were used as methods, and Random Forest was used as a classifier. Based on - cross-validation tests with optimal k values, the model achieved 98.65% accuracy.
Canvas Learning Management System Feature Analysis Using Feature-Oriented Domain Analysis (FODA)
Authors: Wicaksono Galih Wasis , Nawisworo Pamula Brian , Wahyuni Evi Dwi , Cholily Yus Muhammad 
Published: March 2021

Abstract
The impact of Covid-19 on the world of education requires the implementation of online learning. Information and computer technology can provide solutions in education through the Learning Management System (LMS). Canvas LMS is a form of LMS that can be utilized by lecturers and students in online learning during the Covid-19 pandemic. In this study, researchers analyzed the features of Canvas LMS using the Feature-Oriented Domain Analysis (FODA) method. Researchers also conducted a mapping of canvas LMS features with the National Standard of Higher Education (SN Dikti). This study showed two stages of validation by Education and LMS experts to verify the results of the analysis. At the end of the course, we recommended a new LMS feature that complies with SN Dikti for Lecturer and Student users.
Bilingual Lexicon Approach to English-Filipino Sentiment Analysis of Teaching Performance
Authors: Pacol Caren , Palaoag Thelma 
Published: March 2021

Abstract
The aim of this study is to formulate a strategy that can possibly calculate teacher performance by analyzing textual feedback. Expressing textual responses in quantitative form like average sentiment rating can actually provide opportunities for administrators to see if the numerical ratings given complement that of the comments. Our approach was designed to enable processing bilingual textual data. Findings of this study shows that there is strong correlation between teaching performance actual mean rating and average sentiment rating. Furthermore, the approach employed obtained 86% accuracy indicating that it is an encouraging technique, capable of analyzing the students' textual responses. In future work, the use of POS tagging can be explored to improve sentiment analysis accuracy. Employing machine learning methods may also be considered to discover techniques and alternative approaches to sentiment classification.
Comparison of Main Algorithms in Big Data Analysis of Telecom Customer Retention
Authors: Gu Yuanhu , Palaoag Thelma Domingo , Dela Cruz Josephine S. 
Published: March 2021

Abstract
In today’s fierce telecommunications market competition, customer chum is very severe. In order to retain customers, telecommunications companies have made various attempts from various data and consumption characteristics analysis to big data analysis. However, since the actual situation of customer churn is very complicated, how to predict customer churn accurately and quickly is a difficult problem. After the researchers successfully conducted big data analysis of customer churn and successfully retained customers, in this article, the researchers mainly compared several commonly used algorithms in order to find a better algorithm for big data analysis of telecommunications customer churn. Compare and analyze the accuracy and efficiency of these several algorithms and suggest that the business support staffs of telecommunications companies adopt major methods for big data analysis. The researcher found that the Decision Tree (CART) algorithm is better for the prediction of customer churn and guided other branch staffs to predict customer churn and retain customers in a timely manner. This kind of big data analysis can be used to retain customers in the telecommunications industry.
Lightweight Residual Network for Person Re-identification
Authors: Rachmadi Reza Fuad , Nugroho Supeno Mardi Susiki , Ketut Eddy Purnama I 
Published: March 2021

Abstract
In this paper, we investigated several lightweight convolutional neural network (CNN) classifiers for person re-identification problems. Person re-identification can be described as finding a person by performing a query with a specific person image on some defined gallery of people images. We construct the lightweight CNN classifier by utilizing the lightweight residual network architectures originally used for the CIFAR dataset. The goal is to design a lightweight CNN classifier with a maximum of 3 million number of parameters that produce good accuracy on person re-identification problems. The last layer of the residual network is detached and changed by two fully-connected layers, one for learning the discriminant features, and the other fully-connected layer for calculated the final classification score in the training process. Experiment results show that the ensemble of lightweight residual networks achieved a good performance on Market-1501 (rank-1 accuracy of 89.46% with mAP of 84.48% for single-query and rank-1 accuracy of 92.23% with mAP of 88.07% for multi-query). Although the lightweight residual network does not achieve state-of-the-art performance, our analysis shows that the lightweight residual network has higher information density comparing with other state-of-the-art models. More information density means that the classifier is more efficient in terms of performance with the number of parameters in the classifier. Implementation of these experiments are available at https://github.com/rezafuad/ person-reid-lightweight-residualnet.
Fingerprint Salt & Pepper Noisy Image Enhancement with Threshold Method
Authors: Ince Mahmut , Lu Songfeng , Alfadhli Saad Ali , Maulood Ismail , Alresheedi Shayem Saleh 
Published: March 2021

Abstract
We present an adaptive threshold method for salt and pepper noisy fingerprint images. At first, we applied a threshold algorithm to detect noisy and corrupt pixels. Fingerprint image optimized with window filter produced pixels values. We measured the quality of the fingerprint images with peak signal to noise ratio and other efficient noise removing techniques were compared with it. The result shows improving performance of our method with remove salt and pepper noise from a fingerprint image. Our present work is useful to reduce or minimize medium level noise in fingerprint image. In future, we will work to reduce more than 80 percent noise level in fingerprint image.
KaByahe: a mobile application focusing on the historical and cultural places within the city of manila
Authors: Cabrera G M , Caringal L P , Manocan J P , Senga J G , Estrella N 
Published: March 2021

Abstract
With the Philippines' rich historical and cultural heritage, tourism remains a vital sector and is one of the greatest contributors to its rising economy. Manila, its capital, has a vast list of historical and cultural places that mirrors the country’s rich historical and cultural heritage. The developers were inspired to develop a mobile application called KaByahe with the purpose to determine the different historical and cultural places within Manila and serve as its users' own guide in exploring more of its historical and cultural roots. The developers strongly believe that this project is important not only for the benefit of the tourists in exploring Manila, but also, for its local people, to aid them in knowing what has transpired beyond these places and promote appreciation and understanding of the city’s origins. The developers used Agile Development Methodology since the strategy is to develop using short development cycles to focus more on addressing potential issues and produce quality output per cycle. With this, the developers were able to work more efficiently and collaboratively. The developers were able to gather substantial information through various testing procedures conducted to address both functional and nonfunctional requirements. Based on the results of these, KaByahe was deemed to successfully meet the objectives set by the developers.
Ensemble convolutional neural network for robust batik classification
Authors: Azhar Yufis , Mustaqim Moch. Chamdani , Minarno Agus Eko 
Published: March 2021

Abstract
Some researchers propose using the Convolutional Neural Network (CNN) method to classified batik images. It can extract features automatically without the need to define feature manually from the image. However, CNN’s weakness is that its accuracy is quite low, especially for small-sized datasets, compared to machine learning methods that use handcrafted feature extraction. In this research, an ensemble CNN method is proposed to improve the accuracy of the CNN method in classifying batik images. This method will train several CNN models at once, and then by voting and averaging techniques, the output label will be determined. Test results for two different datasets show this method can improve the accuracy of the CNN method and get an accuracy value of 100%. This method is also proven to extract features faster than the state-of-the-art method like MTCD+SVM, which is included in the hand-crafted feature extraction category.
Predicting COVID-19 Confirmed Case in Surabaya using Autoregressive Integrated Moving Average, Bivariate and Multivariate Transfer Function
Authors: Saikhu A , Hudiyanti C V , Buliali J L , Hariadi V 
Published: March 2021

Abstract
In March 2020, the first case of Covid-19 was found in Indonesia. The increase of confirmed, suspected, and exposed in Surabaya has also significantly. Some studies show there is a relation among temperature, humidity, suspected, and exposed patients in an area with the number of confirmed COVID-19. Several statistical techniques that can be used to determine this relationship are to analyze and predict it using the ARIMA, bivariate, and multivariate transfer functions. The aim of this study is the performance of three models and determine the best model. The performance on the training data for ARIMA is 0.376, which shows that the accuracy of the model is 37.6%. The bivariate transfer function accuracy is 0.409, and the accuracy of the multivariate transfer function is 0.478. The result performance of ARIMA testing is 0.074, the bivariate transfer function is 0.055, and the multivariate transfer function is 0.108. The multivariate transfer function forecasting model is a technique in this case with the best performance.
Realization of Ball on Plate Control using PID Controller and Webcam
Authors: Pahlawan Dahnur Agus , Wibowo Agung Surya , Susanto Erwin 
Published: March 2021

Abstract
This study aims to apply the PID controller to the ball on plate control realisation to reach a stable position of ball on plate. The ball on plate props adjust the position at the desired coordinates on a flat square plate. The targeted position is set as set point coordinates in the form of X pixels and Y pixels. The input used is in the form of coordinates obtained from the webcam through image processing methods and sent serially to the microcontroller. The output from the microcontroller is fed into the actuator, namely the servo motor. From the experiment results and its implementation, it is shown that ball on plate can move towards to the desired set point. For PWM signal set point, the value referred to centre of plate is 250 and the response of X-Y axes have errors 3.64% and 8%, respectively.
Usability Evaluation of a Fintech Lending Mobile Application for University Student: A Case Study
Authors: Emanuela Ellen , Widyanti Ari , Pratama Gradiyan Budi 
Published: March 2021

Abstract
The rapid development of information technology has changed various sector of our life, including economy. A number of startup companies in Indonesia has been utilized technology to deliver financial services to its customer. One of them attempts to answerthe needs of university students in Indonesia for an alternative source of funding, who develop a lending mobile application for student. An initial study using interview and secondary data found that the users still find difficulties to use the mobile application. Usability is one approach that can be used to minimize the problem. The purpose of this study is to increase a fintech mobile application’s usability by conducting evaluation of several features including, 'creating a new account', 'completing profile registration', 'applying for university tuition lending', and 'applying for goods lending.' Usability evaluation was conducted by testing the effectiveness, efficiency, and satisfaction through a set of remote usability testing involving 20 participants. The results shows that the mobile application is not optimized in terms of effectiveness, efficiency, and satisfaction as yet. Using the Concept Generation Method, 21 recommendations were proposed to increase the usability of the lending mobile application.
Vehicle Classification Based on CCTV Video Recording Using Histogram of Oriented Gradients, Local Binary Patterns, and Hierarchical Multi-SVM
Authors: Navastara D A , Maulana M F , Suciati N , Sarena S T 
Published: March 2021

Abstract
Vehicle classification is a crucial element in a dynamic traffic management system. The system is needed since the number of vehicles gradually increase every year. There are many methods for vehicle classification, one of those is the use of CCTV camera. As it is multifunction and cheaper than other types of camera, the government tend to use the CCTV camera as monitoring equipment of vehicles on the road. Hence, an accurate vehicle classification system from CCTV records is needed for traffic management system as well as other systems. In this study, the method contains four steps: object detection using Gaussian Mixture Model, features extraction using Histogram of Oriented Gradients and Local Binary Patterns, model training and classification using Hierarchical Multi-SVM. The experimental results show that our proposed method works well with the accuracy of 80.28%, precision of 94.27%, recall of 73.79%, and F-measure of 82.76%.
Scrum Adoption Challenges in Higher Education in Indonesia: Case Study of Board of Information System, Universitas Islam Indonesia
Authors: Setiawan Mukhammad Andri , Sujono  
Published: March 2021

Abstract
The level of success in project development information systems or software in many countries is still low. A study of 110 information system projects in Indonesia found that most information system projects are problematics, and 18% were canceled. Even though it has been around for a while, Scrum as an approach is relatively new in Indonesia’s software development. Many efforts to adopt agile in various organizations are not running well. This research aims to identify the challenges in agile adoption in a higher education organization in Indonesia using the Scrum Adoption Challenges Detection Model (SACDM) theory. The study found that even though Scrum is performing well, there are still some works needed. Especially in improving the experiences and transforming the organizational culture and structure to make the scrum adoption more effective.
Analysis of the dual-fuel combined cycle power plants with a parallel operating scheme efficiency
Authors: Voronkova A S , Borush O V 
Published: March 2021

Abstract
The article addresses the problems of local power plants operating on fossil fuels such as gas and coal. As a solution to the problem, it is proposed to consider dual-fuel combined cycle power plants with a parallel operating scheme. This type of combined cycle technology is good variant for integration into coal predominating districts. Therefore, the efficiency of dual-fuel combined cycle power plants operating at subcritical (p
0 = 13 MPa, t
0 = 540 °C) and supercritical (p
0 = 24 MPa, t
0 = 545 °C) initial steam parameters are discussed in the article. The thermal model and a calculation methodology for the installation under consideration are proposed. The results of the installation’s technical and economic indicators analysis are presented. Additionally article sets out the assessment of capital costs, Net Present Value and the possibility of using the technology under study within the framework of the considering region.
Optimization of refueling times in fast neutron reactors
Authors: Tashlykov O L , Dolgii Yu F , Sesekin A N 
Published: March 2021

Abstract
The importance of solving issues of increasing energy efficiency and energy saving for the development of the Russian economy was emphasized. The main directions of increasing the energy efficiency of the nuclear power industry (increasing the efficiency of using primary fuel and reducing the shutdown time of the power unit for repair and reloading of nuclear fuel) are highlighted. The importance of route optimization in solving applied problems of nuclear power is updated, in particular, in minimizing the time of nuclear fuel reloading, increasing the utilization factor of the installed capacity of NPP power units. The necessity of periodic reloading of nuclear fuel in reactors has been substantiated. The features of nuclear fuel reloading in thermal and fast neutron reactors are presented. The necessity of using in fast neutron reactors a system for guiding a capture on a fuel assembly using eccentrically located rotary plugs is substantiated. The necessity and importance of optimization of the process of guidance and movement of the overload mechanism in order to reduce the time to stop the power unit is shown. Mathematical models for the mechanisms of reloading fuel assemblies have been built. Time-optimal algorithms for the operation of overload mechanisms with two and three rotating plugs are proposed.
Organizing the information security in Modbus TCP interfaces for use in the energy complex
Authors: Ametov F R , Bekirov E A , Asanov M M 
Published: March 2021

Abstract
A modern automated control system at electric power companies is a complex of many systems, modules and interfaces. One of the most important and, at the same time, vulnerable is the switching module, which is a set of devices and interfaces for transmitting, processing and analyzing data. The Modbus protocol is considered in this work as one of the most common interfaces for control systems at power plants. Its advantages and disadvantages are analyzed. Modern control interfaces are susceptible to cyber attacks, which poses a threat to the entire energy complex. The study of Modbus problems is considered, the main solutions for their elimination are proposed and analyzed in order to increase resistance to cyberthreats. A proprietary solution for modernizing the Modbus protocol was proposed based on the implementation of its own authentication mechanism, as well as data transmission using cryptographically strong encryption algorithms. General functional and structural schemes, as well as schemes that take into account the use of the proposed solution, have been formed. The calculation of the cryptographic strength of the proposed cryptography algorithms is made. Conclusions regarding the potential increase in resilience to cyber threats were formulated based on the data collected during the analysis.
Development and modeling of LED indicator of high voltage insulator status
Authors: Balobanov R N , Amirov D I , Razina A G 
Published: March 2021

Abstract
The article discusses a non-contact method for monitoring the state of high-voltage insulation. The principle of operation of circuits of devices built using various electronic components is described. The results of modeling the operation of the device in the software complex of finite element modeling COMSOL Multiphysics are presented. The modeling was carried out by constructing and analyzing three-dimensional models of insulators of the LK70/35 and LK 70/110 brands with indicators installed on them. The presented method of insulation control will allow, during visual inspection of overhead lines, to additionally receive information about the change in the electric field and the appearance of partial discharges in the insulation. The main results of this article are the determination of the parameters and requirements for the electronic components of the considered circuits of indicators of the state of high-voltage insulators.
Transformation Justification of types of filter compensating devices in 6 kV mine networks with powerful nonlinear electric receivers
Authors: Zhilin E V , Prasol D A , Savvin N Yu 
Published: March 2021

Abstract
In this paper presents the features and disadvantages of networks of mining enterprises with a voltage of 6 kV with high-power thyristor DC electric drives of hoisting installations, made according to the TP-D system. In most of these networks, negative phenomena are observed due to the presence of powerful nonlinear electrical receivers. Various power filters are widely used to eliminate negative phenomena and reduce additional power losses in mine networks. Moreover, the choice of a specific type of filter and its design is a complex multicriteria task. The paper presents an in-depth analysis of various types of power filters, and considers factors that influence the choice of FCD. The disadvantages of various existing methods of selecting FCD are revealed. Justification of the types of filter-compensating devices is based on the application of a multi-criteria approach and optimization of the structure of the FCD using the fuzzy set apparatus. The optimal design of FCD for use in 6 kV mine networks with powerful thyristor DC electric drives of hoisting installations, made according to the TP-D system, has been determined. At the same time, the use of the developed FCD design in 6 kV mine networks will allow to compensate for the most pronounced HH currents and voltages, significantly reduce additional power losses, improve the quality of electrical energy and improve the overall electromagnetic environment.
Adsorption Purification of Phenol-Containing Wastewater from Oil Refineries
Authors: Nikolaeva L A , Aikenova N E 
Published: March 2021

Abstract
In this paper, the possibility of adsorptive purification of industrial wastewater from oil refineries from phenols by industrial wastes is considered. It is proposed to use carbonate sludge for water treatment of natural water as one of the most accessible materials, which is a large-tonnage waste of energy, for sewage treatment. Phenols in wastewater are hazardous toxic substances. In legal order, sanitary and hygienic standards establish the maximum permissible concentration (MPC) of phenol in water, which is 0.001 mg / dm3. Industrial wastewater containing phenols has a number of difficulties faced by technologists when selecting a technological scheme for cleaning these pollutants, or their disposal. The adsorption isotherm, the kinetic curve of phenol adsorption, the output curve of phenol adsorption under dynamic conditions were constructed, the dynamic sorption capacity of the “GrSM-1” sorption material was determined, which prove the effectiveness of using carbonate sludge as an adsorbent. A flowchart for the purification of wastewater from phenols is proposed, the calculation of the adsorption filter with the loading of carbonate sludge in the scheme for the purification of wastewater from phenols is performed.