bluuebunny/crossref_metadata_2025 huggingface dataset:
Forecasting Enrolment Data of Surigao del Sur State University, Philippines using Regression Analysis and Multiplicative Decomposition Model
Authors: Maliberan Esmael V.
Published: January 2023

The study endeavored to predict the number of students who will enroll in Surigao del Sur State University using the historic data from 2010-2015. It was accomplished to utilize two existing methods to form its model in forecasting the enrolment data of the University. To project the number of students enrolled at the university, regression analysis, and a multiplicative decomposition model is used. The Mean Absolute Percentage Error (MAPE) of the forecasted enrolment data was 3.10 percent, according to the results. This only demonstrated that the estimated data were similar to the actual data, implying that it is accurate. The predicted enrolment data can be used to support decision-making and as an input to the University Development Plan.
VLSI Architecture for Smart and Precision Agriculture Using Sensors
Authors: Vedulla Tarun. , Reddy Y. Maheswar , Kalyan Achyuta , Jenila R.
Published: January 2023

World population has almost doubled during the last century increasing dramatically the need for food to support the population over 7 billion persons. Precision agriculture is a type of innovative agriculture, based on new technologies, which aims to streamline the agricultural process. Parameters such as temperature, humidity, soil characteristics, and nutrients all play a role in plant development. Numerous sensors are available to measure the environmental factors and depending on datum, the devices monitor and control the parameter changes for each crop. Some existing technologies are more complex and very complicated for farmers to implement. The main goal of this project is to produce precision agriculture-based grid with high performance and low energy consumption.
A Systematic Review of the Adoption of eHealth Cloud-based Technology Applications during COVID-19
Authors: Malatji William Ratjeana , VanEck Rene , Zuva Tranos
Published: January 2023

Electronic health technology applications are important tools that are utilized to provide health care services. These applications allow healthcare professionals and patients to share, manage and have control over their health information electronically whilst maintaining social distancing. Under hard conditions brought by the coronavirus 2019 disease (COVID-19), eHealth tools can be used to assist with the provision of healthcare services. However, the adoption of these technology applications by users is still questionable. This study presents a systematic literature review of 31 articles that were published on the adoption of eHealth cloud-based technology applications during COVID-19. A systematic literature review was conducted using PRISMA protocol by searching the Scopus databases. The search was conducted for the year 2020 to 2021 since COVID-19 is still new in the research field. From 31 articles that were selected, it was found that most countries are still left behind on this topic. It was only a few researchers in each country who tried to contribute or put effort into the topic. Furthermore, it was indicated that Italy contributed the highest with 5 authors to this topic. Thus, more research still needs to be conducted on this topic. One of the limitations of this study was that, the data was gathered from the Scopus database only. Researchers suggest that for future research, other additional sources need to be searched to find out more about the adoption of eHealth cloud-based technology applications during COVID-19.
Catia customization for Design and Modeling of Two stage spur Gearbox
Authors: Patwardhan Mayuresh V. , Nimbalkar Uddhavrao
Published: January 2023

In this paper, we describe how the customization of design task, in solid modeling with CATIA V5 for two stage spur gearbox can be approached, by means of macros (piece of code) and with GUI form. The user has to supply some basic requirements of the gearbox and rest of the different parameters for design of gearbox is calculated by formulas. And then with the help of these parameters, part model of gearbox is created.
A Review on The impact of Transistor Configuration as an amplifier
Authors: Aithekar Vijay
Published: January 2023

In the electronic era, the development of the transistor is unquestionably one of the most valuable contributions in the field of Electronic components. Transistor has an application to work as a switch and as an amplifier and almost in all cases. The transistor is taken as the use of an amplifier because it gives proper biasing. In this review paper, we are going to compare the Transistor as an amplifier with three configurations and select one desirable configuration with perfect amplification & that is CE configuration and taken as used in everywhere mostly.
The Implementation of the Simple Multi Attribute Rating Technique Method for Evaluating the Guidance Process for the Final Project of the Applied Software Engineering Technology Students
Authors: Idmayanti Rika , Meidelfi Dwiny , Rahmayuni Indri , Sukma Fanni , Ramadhani -
Published: January 2023

Simple Multi Attribute Rating Technique (SMART) is a method that is able to solve problems with multi criteria. In the evaluation of the final project guidance process students of applied software engineering technology are intended to identify supporting factors as well as obstacles for students in completing the final project. Used several criteria such as liveliness of guidance, guidance response, how to communicate, mastery of materials, problem solving and report writing. The problem in determining the cause of the hampered completion of the final project is the lack of tools that can help in processing the criteria data. The solution is to utilize the SMART method with multi criteria problem solving as a tool in decision making. With the utilization of this method is expected to provide solutions in evaluating the guidance process so that the results can be accepted by all students objectively. With the decision support system model, it is expected to be able to know the problem factor in completing the final project so as to help in the implementation of the final project in the next period.
Multi-SAP Adversarial Defense for Deep Neural Networks
Authors: Sharma Shorya
Published: January 2023

Deep learning models have gained immense popularity for machine learning tasks such as image classification and natural language processing due to their high expressibility. However, they are vulnerable to adversarial samples - perturbed samples that are imperceptible to a human, but can cause the deep learning model to give incorrect predictions with a high confidence. This limitation has been a major deterrent in the deployment of deep learning algorithms in production, specifically in security critical systems. In this project, we followed a game theoretic approach to implement a novel defense strategy, that combines multiple Stochastic Activation Pruning with adversarial training. Our defense accuracy outperforms that of PGD adversarial training, which is known to be the one of the best defenses against several L∞ attacks, by about 6-7%. We are hopeful that our defense strategy can withstand strong attacks leading to more robust deep neural network models.Deep learning models have gained immense popularity for machine learning tasks such as image classification and natural language processing due to their high expressibility. However, they are vulnerable to adversarial samples - perturbed samples that are imperceptible to a human, but can cause the deep learning model to give incorrect predictions with a high confidence. This limitation has been a major deterrent in the deployment of deep learning algorithms in production, specifically in security critical systems. In this project, we followed a game theoretic approach to implement a novel defense strategy, that combines multiple Stochastic Activation Pruning with adversarial training. Our defense accuracy outperforms that of PGD adversarial training, which is known to be the one of the best defenses against several L∞ attacks, by about 6-7%. We are hopeful that our defense strategy can withstand strong attacks leading to more robust deep neural network models.
A Linguistic Communication Interpretation Wearable Device for Deaf and Mute User
Authors: Rehman Adil , Shoufan Abdulhadi
Published: January 2023

There is a segment of society, which does not have access to today's sophisticated acoustics, but gesture-based sign language, such as using the hands or the shoulders of the eyes, can be a vital tool for making sure their audio is audible. The most widely used sign language in the world, known as ALC—American Linguistic Communication—varies slightly depending on the nation. Deaf and mute people can communicate effectively by using hand gestures to convey their message. The wearable good glove we developed for this study will translate ALC motions into the proper alphabets and words. It makes use of a glove with a number of flex sensors on the fingers' distal and proximal interphalangeal joints as well as the metacarpophalangeal joint to detect finger bending. The complete system is divided into three units: a wearable hand glove unit with a flexible device that records user-created ALC gestures, a processing unit in charge of taking sensor data, and a final unit that uses a machine classifier to identify the appropriate alphabet. In order to receive known alphabet data in text form through a wired channel via the mobile "Sign to Speech App," which presented that text data into this app, the smartphone unit is linked to the processing unit. Its user-friendly design, low cost, and availability on mobile platforms give it an edge over traditional gesture language techniques.
Real-Time Hidden Data Transmission Using Lora
Authors: Satyavathi D.Monica , Mala B.Vandana , Vamsi Ch.Veera , Chiranjeevi Ch.Chiranjeevi , Neeraj Ch.Neeraj
Published: January 2023

Nowadays, it has become a crucial task in transferring confidential data for military departments, many multinational companies, etc.  The important requirement is that the data that has been transmitted should not be visible to hackers or third parties from another end. To satisfy this requirement a wireless technology LoRa is used. Long-distance and low-power wireless communication technologies such as LoRa, Sigfox, and Narrowband-Internet of Things (NB-IoT) were developed in recent years. These technologies can contribute to indoor and outdoor smart applications with minimal power consumption. In this study, the LoRa wireless communication technique was used as the primary data communication method, enabling the device to communicate without requiring an Internet connection or a SIM card. This technology can be implemented in military and defense areas.
Classification of Finger Movements Using EMG Signals with PSO SVM Algorithm
Authors: Pamungkas Daniel Sutopo , Risandriya Sumantri K , Rahman Adam
Published: January 2023

Electromyography (EMG) is a signal produced by human muscles when they contract or relax. This signal is widely used as a controller, for example, to control a robotic arm. This study aims to identify the pattern of finger movement in the form of finger movement using a bracelet-shaped device that has eight EMG sensors. This tool is placed on the lower right hand of a subject to get a signal from the EMG. This study uses the support vector machine (SVM) algorithm combined with the particle swarm optimization (PSO) method. For pattern recognition, the properties of the signal in the time domain are used. From this system, the success of pattern recognition is between 68% to 86%.
Enhancement Support Vector Regression Using Black Widow Optimization for Predicting Foreign Exchange Rate
Authors: Bhagaskara - , Negara Edi Surya
Published: January 2023

Prediction of foreign exchange rates is one of the time series problems that have fluctuating value movements. There are several algorithms that can make predictive models for this problem, one of which is Support Vector Regression (SVR). In this study, foreign exchange rate predictions were made using Hybrid SVR and Black Widow Optimization (BWO). This is done with the aim of improving the performance of the SVR in order to produce a better predictive model for the EUR/USD foreign exchange rate data in 2020. The results of the proposed algorithm get better performance in terms of R2, MSE, RMSE, MAE, and MAPE compared to SVR.
A Nested Monte Carlo Simulation Model for Enhancing Dynamic Air Pollution Risk Assessment
Authors: Hassan Mustafa Hamid , Mostafa Salama A. , Baharum Zirawani , Mustapha Aida , Saringat Mohd Zainuri , Afyenni Rita
Published: January 2023

The risk assessment of air pollution is an essential matter in the area of air quality computing. It provides useful information supporting air quality (AQ) measurement and pollution control. The outcomes of the evaluation have societal and technical influences on people and decision-makers. The existing air pollution risk assessment employs different qualitative and quantitative methods. This study aims to develop an AQ-risk model based on the Nested Monte Carlo Simulation (NMCS) and concentrations of several air pollutant parameters for forecasting daily AQ in the atmosphere. The main idea of NMCS lies in two main parts, which are the Outer and Inner parts. The Outer part interacts with the data sources and extracts a proper sampling from vast data. It then generates a scenario based on the data samples. On the other hand, the Inner part handles the assessment of the processed risk from each scenario and estimates future risk. The AQ-risk model is tested and evaluated using real data sources representing crucial pollution. The data is collected from an Italian city over a period of one year. The performance of the proposed model is evaluated based on statistical indices, coefficient of determination (R2), and mean square error (MSE). R2 measures the prediction ability in the testing stage for both parameters, resulting in 0.9462 and 0.9073 prediction accuracy. Meanwhile, MSE produced average results of 9.7 and 10.3, denoting that the AQ-risk model provides a considerably high prediction accuracy.
Entropy Based Method for Malicious File Detection
Authors: Edzuan Zainodin Muhammad , Zakaria Zalmiyah , Hassan Rohayanti , Abdullah Zubaile
Published: January 2023

Ransomware is by no means a recent invention, having existed as far back as 1989, yet it still poses a real threat in the 21st century. Given the increasing number of computer users in recent years, this threat will only continue to grow, affecting more victims as well as increasing the losses incurred towards the people and organizations impacted in a successful attack. In most cases, the only remaining courses of action open to victims of such attacks were the following: either pay the ransom or lose their data. One commonly shared behavior by all crypto ransomware strains is that there will be attempts to encrypt the victimsâ€™ files at a certain point during the ransomware execution. This paper demonstrates a technique that can identify when these encrypted files are being generated and is independent of the strain of the ransomware. Previous research has highlighted the difficulty in differentiating between compressed and encrypted files using Shannon entropy, as both file types exhibit similar values. Among the experiments described in this study, one showed a unique characteristic for the Shannon entropy of encrypted file header fragments, which was used to differentiate between encrypted files and other high entropy files such as archives. The Shannon entropy of encrypted file header fragments has a unique characteristic in one of the tests discussed in this study. This property was used to distinguish encrypted files from other files with high entropy, such as archives. To overcome this drawback, this study proposed an approach for test case generation by enhancing the entropy-based threat tree model, which would improve malicious file identification. The file identification was enhanced by combining three entropy algorithms, and the test case was generated based on the threat tree model. This approach was then evaluated using accuracy measurements: True Positive, True Negative, False Positive, False Negative. A promising result is expected. This method solves the challenge of leveraging file entropy to distinguish compressed and archived files from ransomware-encrypted files in a timely manner.
A Microarray Data Pre-processing Method for Cancer Classification
Authors: Hui Tay Xin , Kasim Shahreen , Md Fudzee Mohd Farhan , Abdullah Zubaile , Hassan Rohayanti , Erianda Aldo
Published: January 2023

The development of microarray technology has led to significant improvements and research in various fields. With the help of machine learning techniques and statistical methods, it is now possible to organize, analyze, and interpret large amounts of biological data to uncover significant patterns of interest. The exploitation of microarray data is of great challenge for many researchers. Raw gene expression data are usually vulnerable to missing values, noisy data, incomplete data, and inconsistent data. Hence, processing data before being applied for cancer classification is important. In order to extract the biological significance of microarray gene expression data, data pre-processing is a necessary step to obtain valuable information for further analysis and address important hypotheses. This study presents a detailed description of pre-processing data method for cancer classification. The proposed method consists of three phases: data cleaning, transformation, and filtering. The combination of GenePattern software tool and Rstudio was utilized to implement the proposed data pre-processing method. The proposed method was applied to six gene expression datasets: lung cancer dataset, stomach cancer dataset, liver cancer dataset, kidney cancer dataset, thyroid cancer dataset, and breast cancer dataset to demonstrate the feasibility of the proposed method for cancer classification. A comparison has been made to illustrate the differences between the dataset before and after data pre-processing.
A Conversion of Signal to Image Method for Two-Dimension Convolutional Neural Networks Implementation in Power Quality Disturbances Identification
Authors: Berutu Sunneng Sandino , Chen Yeong-Chin , Wijayanto Heri , Budiati Haeni
Published: January 2023

The power quality is identified and monitored to prevent the worst effects arise on the electrical devices. These effects can be device failure, performance degradation, and replacement of some device parts. The deep convolutional neural networks (DCNNs) method can extract the complexity of image features. This method is adopted for the power quality disruption identification of the model. However, the power quality signal data is a time series. Therefore, this paper proposes an approach for the conversion of a power quality disturbance signal to an image. This research is conducted in several stages for constructing the approach proposed. Firstly, the size of a matrix is determined based on the sampling frequency values and cycle number of the signal. Secondly, a zero-cross algorithm is adopted to specify the number of signal sample points inserted into rows of the matrix. The matrix is then converted into a grayscale image. Furthermore, the resulting images are fed to the two-dimension (2D) CNNs model for the PQDs feature learning process. When the classification model is fit, then the model is tested for power quality data prediction. Finally, the model performance is evaluated by employing the confusion matrix method. The model testing result exhibits that the parameter values such as accuracy, recall, precision, and f1-score achieve at 99.81%, 98.95%, 98.84, and 98.87 %, respectively. In addition, the proposed method's performance is superior to the previous methods.Â
Application of Gray Scale Matrix Technique for Identification of Lombok Songket Patterns Based on Backpropagation Learning
Authors: Al Sasongko Sudi Mariyanto , Jayanti Erni Dwi , Ariessaputra Suthami
Published: January 2023

Songket is a woven fabric created by prying the threads and adding more weft to create an embossed decorative pattern on a cotton or silk thread woven background. While songket from many places share similar motifs, when examined closely, the motifs of songket from various regions differ, one of which is in the Province of West Nusa Tenggara, namely Lombok Island. To assist the public in recognizing the many varieties of Lombok songket motifs, the researchers used digital image processing technology, including pattern recognition, to distinguish the distinctive patterns of Lombok songket. The Gray Level Co-occurrence Matrix (GLCM) technique and Backpropagation Neural Networks are used to build a pattern identification system to analyze the Lombok songket theme. Before beginning the feature extraction process, the RGB color image has converted to grayscale (grayscale), which is resized. Simultaneously, a Backpropagation Neural Network is employed to classify Lombok songket theme variations. This study used songket motif photos consisting of a sample of 15 songket motifs with the same color theme that was captured eight times, four of which were used as training data and kept in the database. Four additional photos were utilized as test data or data from sources other than the database. When the systemâ€™s ability to recognize the pattern of Lombok songket motifs is tested, the maximum average recognition percentage at a 0Â° angle is 88.33 percent. In comparison, the lowest average recognition percentage at a 90Â° angle is 68.33 percent.
Image Prediction of Exact Science and Social Science Learning Content with Convolutional Neural Network
Authors: Mambang - , Marleny Finki Dona
Published: January 2023

Learning content can be identified through text, images, and videos. This study aims to predict the learning content contained on YouTube. The images used are images contained in the learning content of the exact sciences, such as mathematics, and social science fields, such as culture. Prediction of images on learning content is done by creating a model on CNN. The collection of datasets carried out on learning content is found on YouTube. The first assessment was performed with an RMSProp optimizer with a learning rate of 0.001, which is used for all optimizers. Several other optimizers were used in this experiment, such as Adam, Nadam, SGD, Adamax, Adadelta, Adagrad, and Ftrl. The CNN model used in the dataset training process tested the image with multiple optimizers and obtained high accuracy results on RMSprop, Adam, and Adamax. There are still many shortcomings in the experiments we conducted in this study, such as not using the momentum component. The momentum component is carried out to improve the speed and quality of neural networks. We can develop a CNN model using the momentum component to obtain good training results and accuracy in later studies. All optimizers contained in Keras and TensorFlow can be used as a comparison. This study concluded that images of learning content on YouTube could be modeled and classified. Further research can add image variables and a momentum component in the testing of CNN models.
Determining Forest Fire Position from UAV Photogrammetry using Color Filtration Algorithm
Authors: Muid Abdul , Evita Maria , Aminah Nina , Budiman Maman , Djamal Mitra
Published: January 2023

Forest fires frequently happen worldwide, especially in the dry season. A forest fire early warning system (EWS) is needed to prevent this disaster. The main part of EWS is the hotspot detection system. On the other side, Unmanned Aerial Vehicle (UAV) technology offers an alternative solution to detect the hotspot for poor satellite image processing accuracy. Remote sensing techniques with UAV working drones are progressively challenging. Drones can provide results in 2D and 3D images with high resolution and real-time. Therefore, in this research, we have used a photogrammetry application from the number of images collected by a UAV with an optimum flight plan for the mission to determine the location of the forest fire. This paper describes remote sensing experiments using drones to detect land fires. The experiment was carried out using a quadcopter drone of the DJI Phantom 4 Pro. The photos are processed using Agisoft Metashape Professional image processing software and become a 2D image. These images captured a fire simulation in a known location. After a high resolution (GSD â€“ Ground Sampling Distance â€“ 0.87cm/px) orthophoto had been generated, a color filtration algorithm detected a hotspot to detect a fire at the exact location. The results are almost zero deviation of longitude and latitude from the real location with 1.44 m2 and 1.06 m2 fire area from 2 experiments. This algorithm program has TPR and FPR are 0,78 and 0, respectively. Further research can develop an EWS with a combination of UAV and Wireless Sensor Networks.
The Small UWB Monopole Antenna with Stable Omnidirectional Radiation Pattern
Authors: Firdaus - , Yuhanef Afrizal , Yulindon Yulindon , Meidelfi Dwiny , Silvana Meza
Published: January 2023

Ultra Wideband (UWB) technology is an unmodulated wireless digital communication system that uses an extremely short duration pulse to transmit information bit. Because of this pulse, the UWB system needs a very wide bandwidth. Federal Communication Commission (FCC) has regulated the 3.1 â€“ 10.6 GHz frequency spectrum for UWB. Since FCC released this frequency, many research in telecommunication have been done on UWB systems. One of them is a development of an Antenna that is suitable for UWB devices. UWB antenna characteristics require FCC band, omnidirectional radiation pattern, and compact size. In order to meet these needs, an antenna with a simple structure in the form of a monopole patch antenna with a similar patch size and ground width has been designed. The antenna is built on an FR4 â€“ epoxy substrate material, with 4.4 dielectric constant and 1.6 mm thickness. The antenna feeding structure consists of two 100 Î© and 50 Î© lines with a wideband impedance matching scheme using tapered side and tapered transformers. The antenna design and optimization processes are conducted using electromagnetic simulation software, and measurements are carried out in an anechoic chamber. Simulation and measurement results show good agreement, and the antenna can work at frequencies 3.5 - 11.3 GHz with a gain of 1.5 â€“ 3.25 dBi and stable omnidirectional radiation patterns. The antenna has dimensions of 27 Ã— 8 Ã— 1.6 mm, which are smaller than the antenna reported in the last research and suitable to be applied on various UWB devices.
Restorative Justice as an Effort to Resolve Excise Crimes Against Cigarettes
Authors: Amrullah Rinaldy , Gustiniati Diah , Andrisman Tri
Published: January 2023

Many crime cases in Indonesian society are settled in courts, resulting in a buildup that can hinder the justice system. Meanwhile, none of the cases concerning excisable goods or cigarettes in the Free Trade Zone, which are handled by Customs and Excise in several areas, have reached the judicial process. This problem can be resolved using the restorative justice mechanism, which prioritizes the concepts of peace, mediation and reconciliation, where perpetrators, victims, law enforcement officials, and the community participate directly in the settlement of criminal cases. Therefore, the formulation of the problem in this research involved the legal position of restorative justice and its application in excise crimes. Normative juridical legal methods, supported by empirical juridical data, were used in this research. The results showed that customs and excise violations can be resolved using restorative justice without the need for a court process.
I francescani cinesi e la traduzione della Bibbia
Con traduzione di Huainian Liu Xutang shenfu e testo cinese a fronte
Authors: De Gruttola Raissa
Published: January 2023

The translation project of the Sigao Shengjing 思高聖經 or Studium Biblicum Version of the Catholic Bible in Mandarin Chinese was undertaken by the Italian Franciscan missionary Gabriele M. Allegra in 1935. In 1945 he decided to gather a group of collaborators and established the Studium Biblicum Franciscanum Sinense (Sigao Shengjing Xuehui 思高聖經學會), an institute in charge of the translation and publication of the biblical volumes, which still operates today in Hong Kong. The single volume of the Bible was published in 1968 and is known with the name of the Studium Biblicum, however, the work of Father Allegra has been explored, while very few details on the Chinese members of the institute are available to date. The contribution of the Chinese friars was fundamental and remarkable in the translation and publication process, and they had an important role in the life of the Catholic Church during and after their work at the Studium. Furthermore, exploring their lives and activities, it must be noticed that their presence would be of primary importance in establishing the Franciscan Vicary, and later Province, of Our Lady of China. This volume considers the Chinese point of view in the experience of the translation of the Catholic Bible in Chinese and the life of the Franciscan Order in China, giving the historical context and outlining the lives and activities of the first ten Chinese members of the Studium Biblicum Franciscanum Sinense, exploring their work in the context of the biblical translation and the life of the Studium Biblicum. In particular, it focuses on Father Ludovicus Liu Xutang 劉緒堂 (1916-1989) whose life and activity details were collected in the booklet Huainian Liu Xutang shenfu 懷念劉緒堂神父, published in 1990. Its translation and comment will support the presentation of the peculiarities and the importance of the Chinese Franciscan Friars in the life of the Chinese Catholic Church in the twentieth century, both in biblical translation and in the issues related to the Franciscan Order.
Educational humanoid robot using 3D printer and Arduino
Authors:   Korean Institute of Smart Media, Kim SukHun , Kim Nam-Ho
Published: January 2023

Among the types of robots, it is not easy to make a robot that walks on two legs. For this, it is necessary to be able to create software that can control precise servomotor settings and various operations. This process is very difficult for beginners and not easy to make because there is no suitable Arduino shield shape for the robot. Therefore, in this study, a method for manufacturing Arduino and plug-in type shield was proposed. In addition, the process of developing a PC control program that can simplify motion control, manufacturing a robot, and setting servo motor values to easily control motion was introduced. It is expected that this will be of great help to novice developers who are interested in making robots.
The Effect of Fraud Hexagon Model on Fraud Financial Statements in Companies in the Financial Sector
Authors: Janah Nuril , Rachmawati Lia , Widaninggar Nanda
Published: January 2023

This study aims to find the effect of the Fraud Hexagon Model on the Financial Statement Fraud. Fraud Hexagon Model consists of Stimulus which is proxied by Financial Target and External Pressure, Opportunity is proxied by Ineffective Monitoring, Rationalization is proxied by External Quality Auditor, Capability is proxied by Change in Director, Ego is proxied by Frequent Number of CEO's Picture, and Collusion proxied by Political Connection. This study uses purposive sampling method, and the number of companies that are sampled in the study are 42 of 105 companies and analyzed by binary logistic regression analysis. The results of this study found that External Pressure, Auditor External Quality, and Frequent Number of CEO's Picture have an effect on Financial Statement Fraud. Meanwhile, Financial Target, Ineffective Monitoring, Change in Director, and Political Connection have no effect on Financial Statement Fraud on companies in the financial sector listed on the IDX in 2016-2020.
The Effect of Non Perfoming Financing and Financing to Deposit Ratio On Return On Assets
Authors: Rahmansyah Ahmad Iskandar , Balqis Nasya Salsabila , Rahajeng Yekti , Elmas M. Syarif Hidayatullah , Masluha Siti
Published: January 2023

Credit and liquidity risk analysis is one of the way to view the health of a bank, especially the development of Islamic bank in Indonesia. Some of previous studies examined the effect of credit risk and liquidity on the profitability of Islamic banks, but the results were not consistent. Therefore, this study uses credit risk (Non Performing Financing) and liquidity risk (Financing to Deposit Ratio) as variables that affect the profitability (Return on Assets) of Islamic banks. The sample of this study is 4 Commercial Banks of Islamic Exchange that listed on the Indonesian stock exchange during the 2014-2018 period.  The research data is the annual report of bank which is obtained from the Indonesian Stock Exchange website and the data is processed by using multiple regression models. The result of this study indicates that Non Performing Financing (NPF) and Financing to Deposit Ratio (FDR) have a negative effect on Return on Assets (ROA).
Evaluation of Deconcentration Funds in the Regional Development Planning Agency (Bappeda) Central Java Province
Authors: Puspitasari Azzahra Salsabila , Novira Alikha
Published: January 2023

Deconcentration funds are one form of the central government to hold an equitable government in each region using the State Revenue and Expenditure Budget (APBN). The implementation of this deconcentration fund is directly supervised by the governor as a representative of the central government which is included in vertical agencies. The research method used in this journal is the CSE-UCLA evaluation model with research approach used using a qualitative approach with documentation, interviews, and observation methods. Most of the data taken are from the results of documentation studies with data analysis techniques, namely data reduction, data presentation, and conclusion. In the use of deconcentration funds in the Central Java Province for the budget year 2021, which is Rp. 1,144,613,000, - (one billion one hundred forty-four million six hundred thirteen thousand rupiah) which among others is used for expenditure on operational goods, expenditure on non-operational goods, expenditure on supplies, service expenditure, and expenditure on domestic business trips. In its implementation, two obstacles occur. The first obstacle is the change in administrative requirements for disbursing deconcentration funds. The second obstacle occurred because of the COVID-19 pandemic, so there were several activities whose implementation was delayed until the situation could be said to be safe to carry out activities.
Editorial
Authors: Mata Delgado Ana Lizeth
Published: January 2023

Editorial del número 25 de Intervención. Revista internacional de conservación, restauración y museología. _____ Editorial from the 25th edition of Intervención. Revista internacional de conservación, restauración y museologia.
El problema de los paisajes desconocidos en la catalogación en línea de los museos nacionales de arte de Norteamérica
Authors: Rabadán Villalpando María Eugenia
Published: January 2023

Este informe académico es parte de una investigación, desde la perspectiva de los estudios visuales, sobre paisajismo de la modernidad y después de ella en la tradición occidental. Se propone analizar, de acuerdo con el estructuralismo de Thomas Kuhn, el cambio de Gestalt visual de principios del siglo xx relativo a la articulación en el arte de un nuevo paradigma. La visualización atraviesa la curaduría y la catalogación de colecciones en línea de los museos nacionales de arte de Norteamérica, cuestionando el diferencial de percepción de la estructuración de lo abstracto y lo conceptual en el paisaje entre estos acervos. No obstante, este estudio encuentra una solución teórica al fenómeno de invisibilidad de las imágenes en los episodios de carácter no acumulativo, propios, nuevamente según el modelo de Kuhn, de los cambios paradigmáticos. _____ This academic report is a part of a research, from the perspective of visual studies, on landscape art of modernity and after it in the Western tradition. This work proposes to analyze, in accordance with the structuralism of Thomas Kuhn, the change in visual Gestalt of the beginning of the 20th century related to the articulation in art of a new paradigm. The visualization cuts across the curating and the cataloging of online collections of the National Art Museums of North America, questioning the differential perception of structuring the abstract and the conceptual in the landscape between collections. However, this study finds a theoretical solution to the phenomenon of the invisibility of images in episodes of a non-accumulative nature, typical of paradigmatic changes, according to Kuhn’s model.
Mapeo de riesgos participativo para patrimonio cultural. El caso de Tehuantepec, Oaxaca, México
Authors: Torres Castro David Antonio , García Souza Paola
Published: January 2023

El presente trabajo da cuenta de las actividades realizadas en Tehuantepec, Oaxaca, México, como parte de un proyecto piloto de reducción de riesgos para el patrimonio cultural local. Su primera fase buscó comprender, mediante la identificación y el análisis de factores de vulnerabilidad, los riesgos que enfrenta ese tipo de patrimonio ubicado en el primer cuadro de la ciudad. Para ello se implementaron métodos y herramientas participativas de evaluación y mapeo, con los que se generó una matriz de riesgo. Algunos resultados son la identificación de los sitios de mayor relevancia cultural y de las principales amenazas a éstos así como el diseño de posibles soluciones, elaboradas desde lo local. Finalmente, se mencionan algunas líneas de trabajo para las fases posteriores. ______ This academic report verse on the activities carried out in Tehuantepec, Oaxaca, Mexico, as part of a pilot project on risk reduction for local cultural heritage. Its first phase sought to understand, through the identification and analysis of vulnerability factors, the risks faced by this type of heritage located in the first square of the city. To this end, participatory assessment and mapping methods tools were used to generate a risk matrix. Some of the results are the identification of the most culturally relevant sites and the main hazards to them, as well as the design of possible solutions, elaborated on a local level. Finally, some lines of work for subsequent phases are mentioned.
Antonio Mateo Borrego (1660-1746): perfilando la figura de un pintor semidesconocido
Authors: Romero Dorado Antonio , Moreno Arana José Manuel
Published: January 2023

A través de documentos y de obras inéditas, el objetivo de este trabajo es dar a conocer para la Historia del Arte la figura de Antonio Mateo Borrego (1660-1746), un pintor de escuela sevillana semidesconocido, nacido en Antequera, formado en Sevilla y activo en Sanlúcar de Barrameda entre 1692 y 1742.
Comparative Analysis of Apriori Algorithm and Hash-Based Algorithm in Market Basket Analysis
Authors: Aldino Ahmad Ari , Rahma Arfinia , Damayanti Damayanti , Setiawansyah Setiawansyah
Published: January 2023

Grocery stores are now experiencing competition in the business world that is getting tighter, making businesses have to think hard in developing strategies to face competition. In developing strategies that benefit companies can take advantage of information technology. Information technology can help business companies in conducting their business. In this case, business companies can utilize the data generated by information systems to assist in decision making if processed correctly; such data can produce valuable information. Data Mining is the process of using artificial intelligence mathematical statistics techniques and Machine Learning to extract and identify useful information and related knowledge from various large databases/ Data  Warehouse  (Kennedi Tampubolon, 2013).   In this study, researchers used a priori algorithm and  Hash-Based  Algorithm to determine consumer spending patterns or consumer shopping cart data used as much as  1023  transaction data with a minimum value of 0.03 and Confidence of 0.5. This study resulted in an Apriori algorithm producing seven rules and forming a combination of 2 items with a rule strength of 13.14% and accuracy of  92.80%. Hash-Based Algorithm 7 Rule developed as many as two itemsets with a rule strength of 14.35%and  formed an accuracy of  107.76%. From  the results of the algorithm, comparison  can be  concluded  that  Hash-Based  Algorithm is better   than  Apriori algorithm
Perbandingan Keacakan Citra Enkripsi Algoritma AES dan Camelia Uji NPCR dan UACI
Authors: Hidayati Layli Nur , Fitriana Gita Fadila , Adam Ipam Fuadina
Published: January 2023

The need for data security arises because of the many threats made by outside parties to retrieve data and use it for personal interests. Security for medical images is carried out because medical images store patient health information data that is confidential. In this study, the image data used specifically uses radiological medical images. There are many techniques and algorithms that can be used to secure image data. This study uses the AES and Camellia algorithms which in their application use several different operating modes. To measure the quality of the encrypted image, the randomness level of the image was tested using the NPCR and UACI tests. Evaluation is used to determine the best algorithm and operating mode for encryption. Based on the measurement of image randomness on AES CBC, AES CFB, AES OFB, Camellia ECB, Camellia CBC, and Camellia OFB with NPCR values for encrypted images of 99.60%, 99.608%, 99.6093%, 99.6296%, 99.6072 %, and 99.6124%. Measurement of image randomness on AES CBC, AES CFB, AES OFB, Camellia ECB, Camellia CBC, and Camellia OFB with UACI values for encrypted images of 34.714%, 34.754%, 34.603%, 34.983%, 34.615%, and 34.707%.
Implementasi Sistem Monitoring Jaringan dan Server Menggunakan Zabbix yang Terintegrasi dengan Grafana dan Telegram
Authors: Husna Muhammad Aliyul , Rosyani Perani
Published: January 2023

The network administrator is a person who is responsible for managing computer networks. One of the duties of a network administrator is network monitoring because errors on the server and services running on the server cannot be known when it happened. This can be difficult if the administrator is far from a surveillance center. A network Monitoring System is a system that helps Network Administrators in supervising and managing computer networks that exist in an agency. By using the system that will be implemented in this research, the computer network monitoring process can be monitored remotely, anywhere and anytime as long as it is connected to the Internet network. With this Network Monitoring System, it is hoped that in the long term PT Cyber Network Indonesia can implement an integrated and well-monitored Internet network system. Test results using Network Monitoring Zabbix, generate real-time data regarding bandwidth usage, problem logs and resource availability.
Smart School Sebagai Sarana Informasi Sekolah di SDIT Ibnu Khaldun Cirebon
Authors: Riyan Ade Bani , Afandi Dwi Teguh , Hartati Tuti , Amalia Dita Rizki , Nurdiawan Odi
Published: January 2023

The need for information in the world of education in this modern era is very important in determining the progress of an institution. By implementing and utilizing information technology can facilitate school institutions in organizing data and will produce a database file that will make it easier for users to access data. However, the use of information technology at SDIT Ibnu Khaldun Cirebon has not been used optimally. This is where the author's desire to create a Smart School application emerged, which is an application that functions as an academic information application to support daily activities at the school.This study aims to improve the quality of schools and meet the needs of schools and parents in disseminating general school information, and student academic information at SDIT Ibnu Khaldun Cirebon.The method used in this research is the research and development method. Data collection techniques in this study using interviews. This research was conducted at SDIT Ibnu Khaldun by involving teachers, principals, students, and parents of students as research subjects.Based on the results of testing with the black box method on the Smart School application, it can be concluded that functionally it produces results that are in line with expectations
Penerapan Augmented Reality Sebagai Alternatif Media Pembelajaran Bahasa Inggris Pada Anak Usia Dini
Authors: Ismawanti Dyah Monika , Utomo Hari Widi , Fitriana Gita Fadila
Published: January 2023

Learning media is a means of delivering subject matter that can channel messages, stimulate thoughts and feelings and a person's willingness to learn. This is where the need for education from an early age, which is based on Law Number 20 of 2003 concerning the National Education System, states that early childhood education is one of the coaching efforts aimed at children from birth to 6 years. Awareness of the importance of mastering foreign languages, especially English in the current information age, has led to efforts to learn these languages from an early age. Therefore, this study aims to provide an alternative solution in early childhood learning media using marker based augmented reality technology. Making this application using Unity and Vuforia. Development for this software uses the Waterfall method. By utilizing AR technology supported by animation, images and sounds can attract children's interest in learning. The results of the tests that have been carried out through black box testing and pre-test and post-test that have been carried out by the correspondent show the results that the percentage figure is 100% which can be concluded that all features can run well based on their functions. The results obtained during the pre-test get an average of 48 while the post-test results have increased by getting an average of 97.5 which shows that the alternative application of English learning media is fun and very suitable for use by users as an effective and efficient learning medium. and of course interesting
Sistem Inventarisasi Barang Dinas Pendidikan Nasional Kuningan Jawa Barat
Authors: Nuryati Neneng , Lasambouw Carolina Magdalena , Djatnika Djoni , Meilinda Lina , Sholahuddin Muhammad Rizqi , Rachmat Setiadi , Harika Maisevli
Published: January 2023

The national education department's inventory record is unique because the goods are in schools under service, not in the office. Inventory complexity has increased due to the procurement of different schedules and reports, not only for internal but also for other institutions concerned. A structured and accessible inventory from anywhere is the right choice for the effectiveness and efficiency of this work. This research aims to design a website-based information system for goods inventory in the National Education Office (DISDIKNAS). The software development method used in this study is the Rational Unified Process. The study results obtained a web-based application that can help DISDIKNAS inventory goods in a structured and accessible anywhere