bluuebunny/crossref_metadata_2025_split huggingface dataset:
The development and analysis of an information system for incentives publication of reputable indexed international journal and national journal (Case study State Polytechnic of Malang)
Authors: Rohadi E , Amalia A , Kusumah D K , Fahrezi G A A , Sabilla W I , Siradjuddin I 
Published: February 2021

AbstractThe research activities in The State Polytechnic of Malang addressed to achieve the output as articles, intellectual properties, and product innovations. The incentives are given to the researchers who publish articles in reputable publishers due to increasing the articles in both numbers and quality. In this work, an information management system of publications is developed and analysed. The system is integrated into the staff database in order to relate with yearly staff performances. In the system, articles are categorized according to classification as International and National publications. Furthermore, both the International and National Categories are classified as a reputable and accredited publisher, respectively. The proposed system has tested by administrators in each unit and randomly staffs as respondents to fill the questioner. The result shows that the management system can be operated by an administrator in each unit and the staffs do not have difficulty to use the proposed system. It means the proposed system can be applied in The State Polytechnic of Malang.
Web application implementation of Android programming learning assistance system and its evaluations
Authors: Syaifudin Y W , Funabiki N , Kuribayashi M , Mentari M , Saputra P Y , Yunhasnawa Y , Ulfa F 
Published: February 2021

Abstract
Currently, Android has been installed on more than 70 percent of the smartphone devices in the world, which has significantly increased the need for Android-based application engineers. Many IT departments in universities and professional schools have included the Android-based programming into the main subjects. To improve Android programming educations, we have developed Android Programming Learning Assistance System (APLAS), a platform to accommodate the students learning Android programming independently. APLAS adopts the test-driven development method to realize automatic validations of students’ answers to the programming assignments. Previously, APLAS has been implemented as a desktop offline application. In this paper, we present a Web application implementation to manage the learning activities online. This implementation consists of three main parts, namely, Validator, Web Interface, and Database System. To evaluate the effectiveness, we offered three learning topics, Basic UI, Basic Activity, and Advanced Widgets, into this Web application, and asked 60 students in Indonesia to solve them. The results showed that the Web application has well been accessed and smoothly utilized by them. The reliability of the validator program was confirmed by handling more than 180 submissions.
Developing vocabulary card base on Augmented Reality (AR) for learning English
Authors: Rozi I F , Larasati E , Lestari V A 
Published: February 2021

Abstract
The application of technology in the world of education can affect the quality of students in understanding learning material because technology is one of the important elements to assist in the teaching and learning process. One educational application that can be developed is Augmented Reality (AR) technology. AR is one of the learning media that can be used to combine virtual objects or objects into a real environment with the virtual world to be able to interact in realtime. English is a foreign language that must be mastered. In learning English, students need to be given adequate vocabulary learning that can be provided through reading or listening activities. The importance of adequate vocabulary in English to support the smoothness of oral communication, where there are 2 things that inhibit the ineffectiveness of oral communication namely students do not have adequate vocabulary mastery and do not know how to use vocabulary in their spoken language. Effective and interactive learning media will facilitate students in learning vocabulary. This research an instructional media based on augmented reality vocabulary cards will be made for learning English vocabulary. Learning English vocabulary developed is a basic vocabulary consisting of object recognition and greeting. The learning media will display real objects and sounds, so that the object looks real and the ease of pronunciation of English consonants correctly.
Designing real-time research data portal of JTI POLINEMA
Authors: Budiprasetyo G , Yunhasnawa Y , Mentari M , Pratama D C 
Published: February 2021

Abstract
Research culture in Department of Information Technology Polinema is always developed continuously every time. In addition, many research titles that are critical of environmental problems are beginning to be seen. The Information Technology Department has an outstanding focus on issues, namely smart systems which include smart education, smart living, smart healthy, smart city and smart tourism. Research resources in the Information Technology Department Polinema are competing to realize that research focus. For this reason, efforts are needed to increase the availability of facilities that are not only material. The fast response can be solved by providing Real-Time Research Data Portal. The contribution of this paper is to design of middle ware on web portals that have high scalability capabilities for providing large data facilities and fast access. Real-time big data processing is the path that will be described in the architecture that will be created and adapted to the needs of the Department of Information Technology Polinema. The results of the latency evaluation test indicated that RabbitMQ allowed us to enforce concurrency, thereby reducing overall RTC by up to 50% compared to traditional HTTP.
Enhancing student interest in learning through the development of serious mathematics games
Authors: Rawansyah R , Pramudhita A N , Pramitarini Y 
Published: February 2021

Abstract
Learning mathematics in Indonesia today has not given the expected results, it is not better when compared to other countries. If a student is active and able to count quickly and carefully in mathematics, then the student will indirectly be easier to solve problems either in mathematics itself or applied in everyday life. The average educator has not used interesting media to improve children’s numeracy skills, there are often difficulties in students’ mathematics learning. Many research contributions are directed at taking advantage of the success of video games and using them to benefit from the education domain. The concept of learning in this research is carried out by utilizing the development of information and communication technology through interesting mathematical game applications through web-based learning. The game is developed using scratch by MIT so that the development process is less time consuming and easier. The game is in form of the quiz that makes students utilize their mathematical skills to get rewards. In that way, the competitiveness of the students also increases at the same time with their numeric ability. This learning has an appropriate value to be a breakthrough to balance current technological developments and improve students’ numerical ability. Because of the mathematics games has a rewards system, it is interesting for students to learn math.
3D reconstruction using Structure From Motion (SFM) algorithm and Multi View Stereo (MVS) based on computer vision
Authors: Kholil M , Ismanto I , Fu’ad M N 
Published: February 2021

Abstract
The development of the Information and Computer Technology (ICT) sector, three-dimensional (3D) technology is also growing rapidly. Currently, the need to visualize 3D objects is widely used in animation and graphic applications, architecture, education, cultural recognition and Virtual Reality. 3D modeling of historic buildings has become a concern in recent years. 3D reconstruction is an attempt to document reconstruction or restoration if the building is destroyed. By using the 3D model reconstruction using Structure from Motion (SFM) and Multi View Stereo (MVS) algorithm based on Computer Vision, it is hoped that the results of this 3D modeling can be utilized as an effort to preserve 3D objects in the Penataran Temple cultural heritage area. This research was conducted by taking as many as 61 images of objects in the Blitar Penataran Temple area. The photos obtained were reconstructed into a 3D model using the Structure From Motion algorithm in the meshroom. This research a trial of the original image with a compressed image for reconstruction is used to compare the 3D reconstruction process from the two input data. From 61 images processed using the Structure Form Motion algorithm, 33 poses of camera pose and 3D points were improved, both original and compressed images. The number of iterations compresses 1.4% less than the original image and takes 43.53% faster than the original image.
Building Information Modelling for clean water and wastewater system in the medium rise school building
Authors: Rofi K A , Hapsari R I , Riskijah S S , Harsanti W , Dharmawan M A , Rahman T 
Published: February 2021

Abstract
Human activities in a building are closely related to the use of clean water. At this time, the concept of a water installation is demanded to be as effective as possible by minimizing the possibility of water waste caused by leakage problems, broken pipes, blocked pipes, and others. However, some concepts still use traditional techniques by depicting 2D models and manual calculations. The method used is a hydraulic analysis with SNI 03-7065-2005 as standard and using Autodesk Revit MEP as modeling and calculating tools. Necessary data are technical specifications, design drawings, and designed plumbing facilities. The system comprises of Domestic Cold Water, Sanitary Grey Water, Sanitary Black Water, and Vent. Building Information Modelling (BIM) is applied to evaluate the effectiveness of the existing design and design its modification as well as to provide the working drawing. The analysis includes analysis of piping system completeness, system crash, flow, velocity, pressure loss. Based on the report, it can be concluded the flow velocity of Domestic Cold Water is 0.7-6.4 m/s which is out the range of standard value. For the pressure, a manual calculation is performed to validate the report results using the Darcy Weisbach equation that has the same value as the report by Building Information Modeling. The cost of the design conditions has a difference of Rp 8.363.608 or eight million three hundred sixty-three thousand rupiah or 0.4% more efficient.
Micro-expression recognition based on motion detection method
Authors: Rosiani U D , Choirina P , Shoumi M N 
Published: February 2021

Abstract
Micro-expressions are emotional representations that occur spontaneously and cannot be controlled by humans. The micro-expression movements are temporary with fast duration and have subtle movements with little intensity. This is difficult to detect with the human eye. Previous studies have shown that micro-expression movements occur in several areas of the face. This study aims to determine the subtle movements in several areas of the face using the motion detection method. We compared the performance of two motion detection methods: the optical flow method and the Block Matching Algorithm (BMA) method. The optical flow method uses the Kanade-Lucas Tomasi (KLT) method and the BMA method uses the Phase Only Correlation (POC) algorithm. Observations were carried out based on region, where the face area was divided into several observation areas: eyebrows, eyes and mouth. Both methods perform motion detection between frames. The KLT method tracks the movement of the observation points on the frame movement. Meanwhile, the POC method matches the blocks between frames. If the two blocks are the same, no motion vector is generated. However, if the two blocks are different, it is assumed that there is a translational motion and a motion vector is generated. Experiments were conducted using a dataset from CASME II with emotional classes of disgust, happiness, surprise, and sadness. The classification accuracy of the POC method is 94% higher than the KLT method of 84.8% which uses the SVM classification.
Object recognition using cognitive artificial intelligence’s knowledge growing system: A preliminary study
Authors: Sumari A D W , Syamsiana I N , Putra D R H , Asmara R A 
Published: February 2021

Abstract
Object recognition has been a challenge for an intelligent system. There have been various approaches to develop such a system by utilizing machine learning especially which are based on neuron that is, neural network and deep learning. Common problems when using those approaches are the first one is dataset availability and the second one is the number of data. Lack of data causes neural-based approaches cannot be well operated, while a small number of data causes low accuracy results on the system. From another point of view, a considered-new technology from Cognitive Artificial Intelligence (CAI) perspective called as Knowledge Growing System (KGS) which may cope with such problems. With the capability to build its own knowledge from nothing, KGS is able to carry out recognition while developing its knowledge regarding the phenomenon it is trying to recognize. In this research, we showed KGS capability to perform object recognition as it is developing knowledge when interacting with such object directly. We did a benchmark on face recognition use-case with some common machine learning methods to show their performance on a small number of data, and KGS showed good results. With 100 feature-set from 5 persons’ face images, KGS achieves Degree of Certainty (DoC) as much as 80% which is the system’s prediction accuracy that enables it recognizing the person based on that-moment data. Even though it is still lower compared to machine learning methods, but KGS shows advantages that it does not require high computational cost because it requires no training and no model development. In this research, we also showed that KGS enables the fast-deployment light-operated object recognition system.
Testing of black chromium coating on low carbon steel
Authors: Hadi S , Buwono H P , Setiawan A , Valeria S S M , Setyawan H 
Published: February 2021

Abstract
The problem lies in the colour resistance of the black chromium electroplating results that are not yet known for its effective test methods. The purpose of this research is to find an effective method for testing colour resistance. The methods used include preparing the specimen from motorcycle rim, black chromium electroplating, heating the specimens in Muffle furnace for different temperatures, cooling the specimen to room temperature, measure and calculate the colour state in order to decide the fading level, corroding the specimen in several acidity solutions from chloric acid, calculate the corrosion rate and analysis of the results. The results of the study in the form of (1) measurements with Colourflex showed that heating the low carbon steel rim for 2 hours at 200°C the colour remained dark black, at 250, 300, 350, and 400°C the colours faded 20, 40, 45, and 60% respectively. (2) corrosion test shows that at pH 3, 4, 5, and 6 the corrosion rate is 0.166, 0.136, 0.122 and 0.107 mm/year which the colour begins to fade at pH 4 and increase for more acid.
Quality by design of optimum parameter to minimize the weight of plastic products
Authors: Hartono M , Gumono G , Wirawan W , Qosim N , Wicaksono H 
Published: February 2021

AbstractThe research aims to control product quality off-line (quality by design) in producing lightweight plastic products for food packaging. The lightweight product is very profitable for the producers due to the efficient production costs. Quality by design was done by designing controlled parameters in the plastic molding process which includes clamping force, holding time, injection pressure, injection speed and injection temperature and their interactions. The plastic material that is made observable is Polypropylene (PP). The response parameter in this study is the weight of the product. The parameter design method used was Factorial Experiment Design with 5 independent variables with different levels of variation. The results showed that the combination of injection temperature and holding time had a significant effect on product weight. To produce heavier products that are in the area above the holding time of 0.4 seconds at any injection temperature. Meanwhile, to produce a lightweight product (under 43 grams) is at a combination of injection temperature below 263 C and holding time of about 0.3 seconds. The standard weight of the product on the plain bucket food packaging for this yogurt container is 42.5 gram.
Control of rotation speed using angle change or effective cross-sectional area of blades on wind turbines
Authors: Yulianto Y , Pracoyo A , Priyadi B 
Published: February 2021

Abstract
To cope with wind changes when the speed is excessive, the turbine needs to be equipped with a speed regulator. To control the turbine rotational speed can be done by changing the variable angle or blade cross-sectional area. Changes in blade angle are automatically followed by changes in blade cross-sectional area. To get a more stable rotational speed, the cross-sectional area of the blades is changed inversely with the wind speed. Experiments were carried out to obtain an effective blade cross-sectional area, in order to obtain a characteristic curve of the change in angle or the effective cross-sectional area of the blade when wind speed changes. Based on the results of this test, a wind turbine prototype has been designed using 3 blades with a maximum area of 0.22 m2 each. The change in angle is automatically carried out by adding a centrifugal pendulum at a position half the radius of the blade length. Control of rotational speed using a centrifugal pendulum is quite effective as a control for wind turbine rotational speed. Although the rotating speed is not very constant, it shows better stability.
HYBRID SHUFFLED FROG LEAPING ALGORITHM WITH PROBABILITY DISPERSAL METHOD FOR TUMOR DETECTION IN 3D MRI BRAINTUMOR IMAGES
Authors: Sirisha P.G.K. , Haritha D. 
Published: February 2021

Abstract
In the medical image study, the brain tumor classification using MRIs is difficult due to the brain’s complicated structure and the high variance in tumor tissues’ position. So, the requirement for useful and specific tumor identification methods is developing for medical recognition and regular medical applications. The conventional brain tumor identification performs anatomical knowledge of irregular tissues in the brain, helping the doctor design approach. The research proposes several techniques for brain tumor identification. This work aims to present brain tumor identification methods based on evolutional intelligence and segmentation. Unusual areas in the brain are identified by using the Expectation-Maximization (EM) algorithm. For segmenting the 3D brain MRI data, this work presents a novel hybrid optimization meta-heuristic called the Shuffled Frog Leaping Algorithm (SFLA) with probability dispersal (i.e., SFLA - Stochastic Diffusion Search (SDS)). The efficacy of the suggested 3D SFLA probability dispersal EM in enhancing the performance of the 3D SFLA tabu EM has been proven by empirical outcomes.
A Review on Detection of Land Use and Land Cover from an Optical Remote Sensing Image.
Authors: Kavitha A.V. , Srikrishna A. , Satyanarayana Ch. 
Published: February 2021

Abstract
Detection of land use and land cover from an optical remote sensing image is an essential research area from the inception of a remote sensing image. Land use land cover maps have numerous applications in agriculture, environment monitoring, urban planning, etc, along with managing various catastrophic events like floods, tsunamis, forest fires, etc. This paper reviewed major techniques for detection of land use and land cover from an optical remote sensing image. Many techniques based on only spectral information, spatio-contextual information and knowledge based methods have been discussed, finally arguing the importance of the techniques based on spatio-contextual information and Mathematical Morphology.
Sentiment Analysis using Neural Network and LSTM
Authors: Srinivas Akana Chandra Mouli Venkata , Satyanarayana Ch. , Divakar Ch. , Sirisha Katikireddy Phani 
Published: February 2021

Abstract
People put their opinions or views on various events happening in the society or world. Twitter is one of the best social networking sites where a huge amount of data generates on the daily basis. These data can be used to classify their tweets based on various sentiments attached to them. Numerous technologies are applied to analyse the sentiments of users. Sentiment analysis needs a very efficient method to manage long arrangement data and their drawn-out dependencies. In this paper, we have applied a deep learning technique to perform Twitter sentiment analysis. Simple Neural Network, Long Short-Term Memory (LSTM), and Convolutional Neural Network (CNN) methods are applied for the sentiment analysis and their performances are evaluated. The LSTM is the best among all proposed techniques with the highest accuracy of 87%. We have collected a Twitter dataset from Kaggle to perform our experiment. The future improvement of the proposed research should include REST APIs and web crawling-based solutions to get live tweets to perform real-time analytics. We have analysed 1.6 million tweets in our research work.
Classification of Breast Cancer using Histology images: Handcrafted and Pre-Trained Features Based Approach
Authors: Kundale Jyoti , Dhage Sudhir 
Published: February 2021

Abstract
Breast cancer has become a critical disease in women. The number of patients with breast cancer is quite high in India. It is of paramount importance to detect the disease in advance. Digital histopathology is one of the most advanced techniques for detection using machine learning. Artificial intelligence is going to be like a sunrise in the field of medicine. Deep neural networks have been successfully applied to the problem under consideration in the past. As, we know the feature extraction is one of the essential and crucial steps in case of classification. In this paper, we compare two approaches, first is feature extraction using traditional Handcrafted based and other is Transfer Learning based model (Pre-trained) for multiclass classification of Breast Cancer using Convolutional Neural Network (CNN) as a classifier. The models are trained using handcrafted features like Seeped Up Robust Features (SURF) and Dense Scale Invariant Feature Transform (DSIFT) techniques, later these extracted features are encoded by Locality Constrained Linear Coding method (LLC). In pre-trained model we have used VGG16, VGG19, ResNet50, GoogLeNet for feature extraction. The maximum accuracy for “SURF+CNN” is 92.88% for Handcrafted feature and in case of Pre-trained “GoogLeNet+ CNN” model gives 94%, both for 400X magnification factor.