bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chaos-based Cryptography: A Brief Look Into An Alternate Approach to Data Security
Authors: Sharif Amer , Intan Raihana Nur , Samsudin Azman 
Published: July 2020

Abstract
The present scale of computing inevitably demanded increased level of data security, which is the concern of cryptography. Security of the cipher depends on the strength of the key and the algorithm used to generate the keys. Many modern cryptographic algorithms are based on Number Theory, but in recent years an alternative approach has been studied which is based on Chaos Theory. Many properties of chaotic systems such as nonlinearity, randomness, and sensitivity to initial conditions bear resemblance to those required by cryptography such as diffusion and confusion. Implementations of chaos-based cryptosystems have been proposed by other researchers and yet the strength of these systems from a cryptographic point of view has not been thoroughly considered. This paper discusses the appeal of chaos-based cryptography, some of the researches already done, and the challenges that this approach faces to be established as a fully secure method for data security.
Relationship of Personal Data Protection towards the Electoral Measures: Partial Least Square Analysis
Authors: Lubis Muharman , Ridho Lubis Arif , Almaarif Ahmad , Amalia Nur Fajrillah Asti 
Published: July 2020

Abstract
The adoption of e-voting in several countries poses certain challenges, which are very similar when electronic means are applied to any activities, such as e-governance or e-commerce. Therefore, some people due to economics, politics or social reasons expect the e-voting use will facilitate and solve previous election’s problem. Unfortunately, the most complex and difficult practical implementation with distinct problems depends on the particular condition or culture. One of essential factor concerning the adoption related to privacy protection. Thus, this study examines the relationship of perceived benefit and privacy concern towards personal data protection by establishing model of formative measurement. For the generalization purposes, a survey questionnaire consists of 4 categories of 45 items was distributed offline and online to approximately 800 people with purposive sampling in selected multicultural cities in Indonesia. The result suggested that the Perceived Benefit (PBen) has the strongest predictive value of ƒ2 and Q2 compare to Privacy Concern (PCon) with 0.212 and 0.083 respectively.
Comparative Analysis of Inter-Centroid K-Means Performance using Euclidean Distance, Canberra Distance and Manhattan Distance
Authors: Faisal M , Zamzami E M , Sutarman  
Published: July 2020

Abstract
Clustering is a method needed to group data or objects based on the required level between data, K-means is one of the clustering methods used that can be used easily in its implementation, there are some additions to this method according to the data center and on the weighting of the distance between data, the weighting of the distance between data on K-Means traditionally can be done using Euclidean Distance, Canberra Distance and Manhattan Distance, making this an analysis of the accuracy generated from the method produced by a combination of the Z-score and Min-Max Normalization methods, and is carried out Cluster homogeneity test using the Silhouette Coefficient method. The results of this method show that the Canberra method is superior to Euclidean and Manhattan on Iris dataset and the Canberra combination method with Z-score and Min-Max can increase the value on the glass without using the Normalization Method 37. 44% to 67.46% use the Z-score and 56.52% use Min-Max and use an increase in the average value of the Silhouette Coefficient.
Exercising the Students Computational Thinking Ability using Bebras Challenge
Authors: Zamzami E M , Tarigan J T , Zendrato N , Muis A , Yoga A P , Faisal M 
Published: July 2020

Abstract
In this paper, we present our observation regarding the student’s computational thinking skill in the region of Sumatera Utara, Indonesia. The observation is based on the result of Bebras Indonesia 2019, a computer-based countrywide test on computational thinking aimed at students in primary school, middle school, and high school. We collected the data in a specific targeted region (the province of Sumatera Utara), collects additional data from the participant’s school, and analyse the data. Our objective is to find a pattern between the schools’ approach, if any, regarding topics related to computation thinking to the ability of students to actually solve the problem based on their score in the test.
End-to-end indonesian speech recognition with convolutional and gated recurrent units
Authors: Adiwidjaja Rifqi , Ivan Fanany M 
Published: July 2020

Abstract
Automatic Speech Recognition has penetrated deeply into our life. For well-resourced language, it can be considered as solved, but that’s not the case for under-resourced language like Bahasa. Although it’s the 7th most spoken language in the world, the research of speech recognition for Bahasa was still extremely limited, with setting still inconvenient for the real world and industry. This research is an attempt to make a speech recognition model that has applicability to the real world and industry, specifically that supports sentence level input with variable character length with end-to-end training. We built the model using the deep learning approach, specifically utilizing the residual networks and Bi-Directional Gated Recurrent Unit (Bi-GRU). To the best of our knowledge, this is the first Indonesian ASR model that can be trained in an end-to-end manner. Our model surpassed the baseline model on all metrics and achieve competitiveness with the current best result, which used the visual modal, for the dataset even with a more difficult and prone to noise modality like sound.
A Latent Semantic Analysis Method for Automatic Scoring System at Essay Test
Authors: Handayani L , Alika W O , Negara B S , Febiyanto  
Published: July 2020

Abstract
An essay test is the type of test that requires students’ skills to propose, arrange, and combine the ideas they have from the teaching-learning process conducted. The essay answers in the form of description cause the examination becomes more complicated compared to an objective multiple-choice test. Therefore, in this research, the scoring system is built for an essay test by Using Latent Semantic Analysis that can pay attention to the word synonym of the key answer on the students’ answer. The highest accuracy from the test that had been conducted at the essay scoring system by Using Latent Semantic Analysis was 84.35%, categorized into good.
Genetic Algorithm in Image Inserting with Modified Least Significant Bit Method to Find The Best MSE Value
Authors: Ramadhan S F , Sihombing P , Sutarman  
Published: July 2020

Abstract
Inserting data into digital media tends to change the large size of the media cover file, this is because the inserted pixel has a different size from the insertion value, i.e. with a larger or smaller value, for example a pixel value of 10 is inserted with larger or smaller data from the value 10. So that the pixel value is getting further from the value of 10, this causes the value of Mean Squared Error (MSE) of the media of the cover (cover) to become larger. In this study, the selection of pixels in the image is in accordance with the value of the insertion data as the insertion place with the Genetic algorithm (GA). Insertion of data on selected pixels using the GA algorithm is performed using the Modified Least Significant Bit (MLSB) algorithm at the position of the least significant bits. To find out the reliability of the proposed algorithm, the data insertion experiment was carried out by comparing the conventional LSB algorithm with the proposed algorithm where the results obtained a significant MSE value, i.e. the average MSE value of the LSB algorithm was 20.54 and the proposed algorithm was 7.12.
Optimization DataTransfer Using the Neural Network method Based on Signal Level
Authors: Zendrato Niskarto , Zarlis M. , Salim Sitompul Opim , Muisa Zamzami Elviawaty 
Published: July 2020

Abstract
The use of the internet that is very high at this time in all fields requires continuous development to improve the quality of data transfer. By improving the quality of data transfer, all activities that use the internet for transactions can run well. Good data transfer is influenced by speed, while speed is influenced by strength. There are several things that affect the data transfer process, but this research only focuses on speed and signal. Neural Network algorithm is used to determine the optimal point of the signal, where the optimal signal point is the maximum data transfer rate. This algorithm can be used to determine the optimal point with an accuracy rate of 10%
Performance Improvement of Clustering Affinity Propagation Method using Principal Component Analysis
Authors: Simanullang Jasael , Zarlis Muhammad , Muisa Zamzami Elviawaty 
Published: July 2020

Abstract
Affinity Propagation Method it is necessary to modify the algorithm by using Principal Component Analysis (PCA). PCA method is used to reduce the attributes or characteristics that are less influential on the data so that the most influential attributes are obtained to then be carried out the clustering process with Affinity Propagation. The comparison results of the PCA + AP grouping model have better performance than the conventional AP grouping model. This is justified because the number of iterations and clusters produced by the PCA + AP clustering model does not change and converges when there are 8 optimal cluster clusters. While the performance of conventional clustering models produces an optimal number of clusters from 14 clusters with a significant number of iterations. So it can be concluded that the PCA + AP grouping model is suitable for the Air Quality dataset because it produces an optimal number of clusters and iterations of 8 clusters. The comparison results of the PCA + AP grouping model have better performance than the conventional AP grouping model. This is justified because the number of iterations and clusters produced by the PCA + AP clustering model does not change and converges when the optimal number of clusters is 5 clusters. While the performance of conventional clustering models produces a suboptimal number of 10 clusters with a significant number of iterations. So it can be concluded that the PCA + AP grouping model is suitable for the Water Quality Status dataset because it produces an optimal number of clusters and 5 cluster repetitions.
Counter-propagation Neural Network for Brain Tumor Classification
Authors: Rahmat R F , Harahap Y T A , Rachmawati D 
Published: July 2020

Abstract
Brain tumor is a condition in which abnormal cells grow unnaturally in the brain. Depending on the size and type, the abnormal cells called tumors can be life-threatening if the patient does not take immediate treatment. The cause of tumor growth in the brain is the presence of risk factors such as family history and ionization radiation. Patients with brain tumors will experience several symptoms of a headache, nausea, memory loss, and changes in vision, speech, and hearing. Detection of brain tumors can be performed with the help of the medical device of Magnetic Resonance Imaging (MRI) Scan. Through the image of MRI Scan results, radiology specialists will interpret and analyze the brain condition. However, analysis and conclusions for this matter take a long period of time. Therefore, a method is required to classify the brain tumors through MRI images automatically. The method used in this research is Counter-propagation Neural Network. Prior to classification, the brain’s MRI image will be used as the input for the image pre-processing stage then go through the segmentation and feature extraction processes. Based on the test, it can be concluded that the proposed method can identify brain tumors with an accuracy of 92.5%.
Classification of Infection Type Based on Leukocytes Examination Results Using K-Nearest Neighbor
Authors: Suyanto S A N , Siregar B , Nababan E B , Fikri H A 
Published: July 2020

Abstract
Leukocytes are blood cells that contain nuclei, also called white blood cells. Leukocytes have a role in the cellular and humoral defiance of organisms against foreign substances. Laboratory tests of blood samples greatly influence the diagnosis of a disease. Manual blood tests do have a low price but still have some weaknesses such as the length of time needed will be longer, because health practitioners must examine them carefully to avoid misinformation. To help overcome these weaknesses, a classification of types of infections was carried out based on the results of leukocyte examination. Classification is a grouping of data where the data used has a label or target class. So that the algorithms for solving classification problems are categorized into supervised learning. The purpose of supervised learning is that label data or targets play a role as a ‘supervisor’ or ‘teacher’ who oversees the learning process in achieving a certain level of accuracy or precision. The algorithm used in this study is K-Nearest Neighbour. The data used in this study as many as 2,098 results of complete blood tests taken from one hospital in Medan. This study resulted in a classification accuracy of 92%.
Descriptions of reservoir basin subsurface structure in UNNES based on microgravity data
Authors: Supriyadi S , Khumaedi K , Setiawan F , Yani M , Mukromin T M 
Published: July 2020

Abstract
UNNES reservoir basin as a characteristic of the Conservation University is around 12 years old. This relatively long span of time has never been carried out a physical study of a subsurface structure. This study aims to describe the subsurface layer based on gravity data. The method used is to use gravity by calculating the elevation of each measuring point and by tidal correction and drift correction. Both of these corrections are to reduce the tidal and fatigue effects of the gravimeter. Measurements were done in July 2019 (dry season). The results of the study based on observational gravity data indicate that the value of a large gravity is in the north-south part and the smallest value is in the west part of the reservoir basin. The structure of the first layer which has an average density of 2.7 g/cm3 thick 75 m below the surface. The second layer is dominated by andesite rock with an average rock density of 2.8 g/cm3 thick 50 m below the first layer. While the lowest layer is a layer dominated by basalt rock with an average rock density of 3.1 g/cm3 thick more than 40 m below second layer.
Influence of annealing duration on structural, optical and electrical properties of AZO thin films grown on corning glass by dc magnetron sputtering
Authors: Sugianto S , Astuti B , Marwoto P , Firmahaya N A , Aryanto D , Isnaeni  
Published: July 2020

Abstract
Al doped ZnO (AZO) thin films were deposited using dc magnetron sputtering on corning glass substrate has successfully done. After deposition, the samples were annealed in vacuum ambient at temperature of 300 °C with variation in annealing duration of 0, 30, and 50 minutes, respectively. The structural, optical and electrical properties of these films have been investigated as a function of annealing duration. Thin films were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), UV-Vis spectrometer and I-V measurements. AZO thin films without annealing treatment was showed amorphous structure. However, after annealed at 30 and 50 minutes, the films obtained were polycrystalline with a hexagonal wurtzite structure and preferred orientation in the (002) plane. Average optical transmittance of the AZO thin films was over 85%. In Addition, the electrical resistivity is reduced from 1.85 × 106 Ωcm to 1.93 × 102 Ωcm when applying annealing treatment. It’s can be concluded, the annealing treatment in vacuum ambient was improved the crystallinity and simultaneously improved optical and electrical properties of AZO films.
X-ray diffraction studies of ZnO:Cu thin films prepared using sol-gel method
Authors: Astuti B , Zhafirah A , Carieta V A , Hamid N , Marwoto P , Sugianto  , Nurbaiti U , Ratnasari F D , Putra N M D , Aryanto D 
Published: July 2020

Abstract
ZnO:Cu thin films were deposited on corning glass substrate using sol gel method with different concentration of Cu (0, 1, 3, and 5%) has been done. The effect of the different Cu concentration on the structural properties of these films was studied in detail. Based on the XRD result, the ZnO thin films undoped and doped Cu are polycrystalline with hexagonal wurtzite structure and has preferred orientation is c-axis. All peaks of ZnO thin films undoped and doped Cu shows that reflection peaks associated with (100),(002) and (110) planes. The film quality was improved with the increasing of the Cu concentration. The value of the lattice constant a and c was found to be increased with increases of the Cu concentration. Changes in the lattice constant affect the bond length of ZnO (L) and the volume of one hexagonal system unit (V). The lattice parameter also affects to the crystallite size. The crystallite size was increased with Increasing of the Cu concentration and the lattice parameter. Furthermore, the strain value of the film decreases with increases of the Cu concentration. Lattice strain that has decreased is due to the cavity around of the formed film. Cavities between atoms also affect the density of the dislocation. The larger cavity between atoms on the films that makes the dislocation density becomes smaller.
Identification of subsurface layer in UNNES reservoir basin
Authors: Supriyadi S , Khumaedi K , Mukromin T M , Yani M , Setiawan F 
Published: July 2020

Abstract
Reservoir basin is one of the important components in water conservation which is very supportive in Green Campus activities. The importance of information on the sub-surface layer surrounding the reservoir basin is the first step in managing and empowering the location. The purpose of this research is to identify the subsurface layers in the UNNES reservoir basin. The method used in this research is the resistivity geoelectric method with the Wenner configuration. Measured track totaling three which is located on the side of the UNNES reservoir basin with a track length of 75 m. The results of the identification of the subsurface layer get four layers, namely the layer of tuff sand/water with a value of 1.22 - 2.79 Ωm, a layer of clay with a value of 6.41 - 14.7 Ωm, a layer of sand / gravel with a value of 33, 7 - 77.3 Ωm and lava flow / breccia flow with a value of 77.4 - 177 Ωm.
Quantum oscillators model to derive an ideal gas in Bose-Einstein condensates under gravitation of earth
Authors: Prayitno T B 
Published: July 2020

Abstract
Considering a set of condensates as N indistinguishable noninteracting quantum oscillators and replacing an available volume with a harmonic volume, we derived an ideal gas model by applying the canonical partition function via the thermodynamic relation. In this case, we take a longitudinal part of the three-dimensional Gross-Pitaevskii equation in which the effect of gravitation of earth works. Since we used the time-independent perturbation theory, to include gravity effect, we must put the higher coefficient in the formulation of each energy state whose value is determined by the separated amplitude formula in each state. It will also be shown that even though the equation of state represents an ideal gas, the appropriate heat capacity approaches Einstein’s solid-like model if the certain conditions are employed.
Development of teaching materials for momentum assisted by scratch: building the pre-service teacher’s skills for 21st century and industry revolution
Authors: Rusilowati A , Subali B , Aji M P , Negoro R A 
Published: July 2020

Abstract
Learning physics problems still appear in many parts of the world. Along with this, the development of civilization demands the development of education to produce the skills that are the ultimate in every human being. 21st Century skills are skills that are relevant to the demands of the development of civilization. Pre-service Teacher needs to be prepared to overcome the problems of learning Physics by following with the times. This study aims to develop a skill-oriented Momentum teaching material of the 21st Century and the industrial revolution. This research is development research with stages: 1) Analysis of potential and problems, 2) Product design, 3) Design validation and design revision, 4) Product testing, 5) Analysis of trial results, and 6) final product assembly. The research instruments were in the form of observation sheets, tests, and questionnaires. The data analysis technique uses descriptive percentages. The results of the study in the form of scratch-assisted teaching materials that have characteristics provide opportunities for students to make momentum simulations independently. The percentage of the material validity score was 92.23% and the media validity was 88.64%. The results of the trial show that the acquisition of each skill score is more than 71, so it can be concluded that the materials teaching developed are practically used and effective to build 21st-century skills and industrial revolution 4.0.
Analysis of student’s learning achievement using PhET interactive simulation and laboratory kit of gas kinetic theory
Authors: Rustana C E , Andriana W , Serevina V , Junia D 
Published: July 2020

Abstract
This Quasi Experimental research aims to analyze the learning achievement of grade XI students of Public Senior High School in Bekasi, West Java-Indonesia. Two experiment science classes were selected as samples by using purposive random sampling. The 1st sample class was taught using laboratory kit activity; whirls the 2nd sample class was using PhET interactive simulation. The data was collected using written test to measure students’ achievement and then statistically analyzed using t-test to determine the hypothesis either be accepted or not. The normal distribution and homogeneity tests were also applied to know that the data was normally distributed, and all the variances were homogeneous with level of significant >0.05. The t test result indicated that the value of tcalculation (3,052) was greater than and tTable (1,667) that shown that there was a significant difference between the learning achievement of class 1 and 2 with mean value of 70.85 and 63.26, respectively. In conclusion that learning process using PhET interactive simulation provided higher students’ achievement compared to those class which apply laboratory kit activity of gas kinetic theory.
Investigation of the physics phenomena of weakly damped wave equations with forced force: theory and simulation
Authors: Jufriansah A , Hermanto A , Toifur M , Prasetyo E 
Published: July 2020

Abstract
The perturbation method is used to see changes in solutions that occur when attenuation is of little value, as in the phenomenon of waves with weak attenuation and which subjected to coercive force. Therefore this study aims to find solutions to solve the wave equations that experience weak attenuation and which subjected to coercive force. The method used is the study of literature and computation with MatLab. Based on the research results obtained that analytically non-homogeneous waveforms can not provide general solutions for differential resolution. Whereas computationally the results obtained are, the wave model with weak attenuation and the wave model with coercive force have amplitude values that change for time and for time wave models that subjected to coercive force has an amplitude value that increases compared to without coercive force.