Reviewerly/exHarmony huggingface dataset:
AUTORSKOPRAVNA ZAŠTITA UMETNIČKIH DELA STVORENIH VEŠTAČKOM INTELIGENCIJOM

Artificial intelligence today finds application in a field that until recently was reserved only for creative people. It is a visual art. For many people, artists still play a major role in the creative process. However, artists working with artificial intelligence do not create the artwork themselves, but develop software that in turn creates the work. Some artists see artificial intelligence systems only as a tool to work with, while others see these systems as a "colleague" with whom they create their works. In the paper, the author deals with the question of whether artificial intelligence in visual art becomes an artist itself or is it just another technical tool for creating author's works.
IMPLEMENTASI METODE TOPSIS PADA SISTEM PENDUKUNG KEPUTUSAN SELEKSI PEMBERIAN PINJAMAN BADAN USAHA MILIK DESA (STUDI KASUS : DESA BATU NAMPAR INDUK)

The selection process for granting loans to BUMDes Sinar Linus is done conventionally, in this case it makes researchers feel interested in designing a WEB-based Decision Support System as a decision support tool for members of BUMDes Sinar Linus. The methodology used in the development of this system is a method of collecting data in the form of observation, interviews and literature study. While the analytical method used is the TOPSIS (Technique For Others Reference by Similarity to Ideal Solution) method as a decision-making method for the design method using Extreme Programming (XP) which includes planning, design, coding and testing stages. And for the testing method using Blackbox Testing includes home display, login, loan application, applicant, criteria, alternative and TOPSIS. This research resulted in a web-based decision support system that can facilitate members of the BUMDes Sinar Linus in Batunampar Village in deciding or determining prospective recipients of loan funds at BUMDes Sinar Linus.
PERANCANGAN WEBSITE MARKETPLACE BERBASIS PHP DENGAN FRAMEWORK CODEIGNITER

The development of marketplace-based online trading facilities has been widely circulated in Indonesia. However, there are no services to provide marketplace-based jobs. Even though this service is really needed by the community, especially with the increasing number of unemployed in Indonesia. These employment services are website-based so that people don't have to go to each company, just stay at home and attach several files as support to get a job. With this application, information on job vacancies in an area can be disseminated on this system. This freelance marketplace distribution system was built using the waterfall method with four stages of applicable methods, namely requirements analysis, system design, implementation, and system testing using the PHP and Condigniter 3 programming languages. , ordering, talent details, logout.. On the other hand, the advantages of looking for a job online are that apart from being flexible, it can also open up new and broad opportunities. And it can reach various aspects of society.
SISTEM INFORMASI PENDATAAN PENDUDUK DESA DETUSOKO BARAT KECAMATAN DETUSOKO KABUPATEN ENDE BERBASIS WEB

The village office of West Detusoko is one of the government agencies that serves the community directly in collecting data on the occupation. Population data collection in the village of West Detusoko currently uses computerization, namely using Microsoft Word and Microsoft Excel application programs. but there are still many errors and the possibility of data loss, input errors, doubling of data input and the difficulty of searching for population data so that it takes a long time and causes delays in making reports. The purpose of this study is to build a population data collection information system using language PHP programming and database In this study the author uses a qualitative descriptive approach. The software design method used is the waterfall method. The testing method used by the author is blackbox testing. With this information system, it can help overcome the problems of population data collection in West Detusoko Village.
IMPLEMENTASI STRUKTUR DATA TREE PADA WEB BLOG SEBAGAI MEDIA PEMBELAJARAN

In writing this study aims to review the implementation of tree data structures on web blogs as learning media, starting from a discussion of the implementation of data structures. After that, it was continued with the use of blogs as an applied learning medium. The use of tree data structures is one of the most common data structures used in the development of a web. One of the efforts to streamline and provide a variation in the realm of learning media is to create a web blog, especially in the era of globalization, everyone who lives in that era should at least know about one of the results of technological and communication advances. This study will see how the description or description of the application of tree data structures on blogs as learning media. The making of this research uses a qualitative descriptive method in which the data is obtained from observation and documentation of matters relating to the topic under study. The core discussion of this research is the implementation of data structures on blogs as learning media.
PERANCANGAN BASIS DATA PENJUALAN PADA KONVEKSI RAFKA BABY

Rafka Baby Convection is an industrial business that produces baby clothes that has been established since 22 years ago. Sales data collection at the Rafka Baby Convection is still done manually. This study aims to find out what are the needs and problems in sales data collection and to design a sales database in developing the Rafka Baby Convection business. The method used in this study is the method of data collection by interview and literature study, as well as the system design method, which means the author designs a new database system based on the results of data collection. The results show that sales at Rafka Baby Convection are still manual in the sense that sales are made without a database system regarding the goods sold, buyers, payments, and transactions. Therefore, a database design was made to help collect data on the Rafka Baby Convection. The database created is designed using a MySQL database and is managed in the PhpMyAdmin application. This database design is expected to be able to provide convenience in collecting sales data at Rafka Baby Convection.
COMPARISONAL ANALYSIS OF MYSQL AND MONGODB RESPONSE TIME QUERY PERFORMANCE

Query is the ability to display and or request data that is used to access data in the database system by using certain commands. Where a data obtained from one or more tables in the database according to what the user needs. The data can also interact with other data or tables with the aim of making it easier for the user to use it. The query response time is one of the considerations for testing databases. This journal will discuss two types of databases, namely MySQL (SQL) and MongoDB (NoSQL). Due to the increasing demand for data, data processors are competing to provide the right database with the best performance for applications or data processing. Then this journal provides a comparison analysis of MySQL and MongoDB databases in response time performance. This study uses the Query Runtime comparison execution test method between these databases. By using basic commands or DML queries, namely CRUD (Create, Read, Update, Delete). Several stages will be carried out, namely the determination of the dataset, implementation and testing, and analysis of the test results. In this study, trials were conducted on the insert, select, update, and delete processes with the data being tested were 100, 1000, 10000. After experimenting with MongoDB (NoSQL) and MySQL(SQL) databases. The MongoDB database has a faster query response time in the insert and delete process, for the query response time update and delete the MySQL database has a faster response time. Then it can be obtained that in query response time, the MongoDB database is superior in the update and delete processes with a runtime difference of 0.005 seconds and 0.017 seconds. MySQL database is superior in insert and select process with a difference of 4.137 seconds and 0.006 seconds.
Guidance and Counselling Service: A Path to Enhance Academic Achievement for Secondary Schools’ Students

This article focuses on the importance of guidance and counselling services for improving learning outcomes of students in the secondary schools of Larkana Division. Guidance and counselling service is supportive to students in aligning their strengths, enhancing their learning outcomes, nurturing their interests and values, and ultimately facilitating the realisation of their complete potential. In present era of information technology it has become difficult for a student to take right direction in educational perspective. The need of a counsellor is felt more than ever. By using a quantitative study approach a questionnaire was developed to collect data from 200 Male and Female secondary school students of Larkana Division, Sindh, Pakistan. The study showed the need of strengthening teacher-pupil interaction, considering student subject selection and feelings, and addressing concerns related to exam challenges and curricular relevance. The Ministry of Education must develop counselling centres in both public and private secondary schools, as well as the implementation of comprehensive counselling curricula.
Teachers' Perspectives on Digital Transformation and Hybrid Models in English Language Education

This study investigates educators' responses to digital transformation and the challenges and opportunities posed by the hybrid learning model. Drawing from a sample of 100 instructors in Multan's Federal Government schools, the research underscores the imperative for robust teacher training programs aimed at enhancing proficiency in the evolving landscape of hybrid learning. The study advocates for continuous training initiatives and proposes policies mandating up-to-date technology integration training for all teachers. In an era marked by technological revolutions, the research emphasizes the growing dependence on digital systems, calling for official endorsement and support of research in hybrid learning and digital transformation. Such initiatives seek to optimize technology utilization within classrooms, fostering competence in the hybrid learning model and cultivating a more resilient and adaptable education system. Ultimately, understanding and addressing teachers' perspectives on hybrid learning and digital transformation are deemed crucial for creating an educational environment that excels in an increasingly digital world.
DAMPAK ARTIFICIAL INTELLIGENCE TERHADAP PEMBELAJARAN IPA/FISIKA DI SEKOLAH

The evolutionary era of Industry 4.0. and the era of society 5.0. make changes to learning activities at school. The use of science/physics learning media, methods and models based on Artificial Intelligence is able to visualize science/physics learning material which is mostly abstract in nature. The teacher's role in making science/physics learning activities effective, interactive and communicative is very large. For this reason, teachers need to increase their insight and upgrade their knowledge of Artificial Intelligence-based digital technology so that learning objectives can be achieved effectively. Of course, the application of Artificial Intelligence in accordance with the material taught in science/physics lessons will make learning activities more interesting and have a positive impact on the progress of education in Indonesia. Even though the positive impact of Artificial Intelligence is more dominant than the negative impact, it is necessary to anticipate the negative impact of using AI in science/physics learning so that progress in the education sector becomes more efficient, effective and safe in the future.
A Brief Introduction to Infrastructure Planning for Next-Generation Smart Computing Data Centers

Globally, digital technology and the digital economy have propelled technological revolution and industrial change, and it has become one of the main grounds of international industrial competition. It was estimated that the scale of China’s digital economy would reach 50 trillion yuan in 2022, accounting for more than 40% of GDP, presenting great market potential and room for the growth of the digital economy. With the rapid development of the digital economy, the state attaches great importance to the construction of digital infrastructure and has introduced a series of policies to promote the systematic development and large-scale deployment of digital infrastructure. In 2022 the Chinese government planned to build 8 arithmetic hubs and 10 national data center clusters nationwide. To proactively address the future demand for AI across various scenarios, there is a need for a well-structured computing power infrastructure. The data center, serving as the pivotal hub for computing power, has evolved from the conventional cloud center to a more intelligent computing center, allowing for a diversified convergence of computing power supply. Besides, the data center accommodates a diverse array of arithmetic business forms from customers, reflecting the multi-industry developmental trend. The arithmetic service platform is consistently broadening its scope, with ongoing optimization and innovation in the design scheme of machine room processes. The widespread application of submerged phase-change liquid cooling technology and cold plate cooling technology introduces a series of new challenges to the construction of digital infrastructure. This paper delves into the design objectives, industry considerations, layout, and other dimensions of a smart computing center and proposes a new-generation data center solution that is “flexible, resilient, green, and low-carbon.”
The Influence of Information Technology Based Audit Procedures and Audit Experience on Audit Quality

The Ministry of Finance as one of the regulators in Indonesia has also issued regulation Number 186 /PMK.01/2021 concerning the Development and Supervision of Public Accountants which is effective on March 15 2022 (Janah et al., 2022). This regulation did not appear without reason. Several cases related to audited financial statements have occurred in recent years. Some of the financial reports that are cases include the financial reports of PT. Garuda Indonesia Tbk which was audited by the Public Accounting Firm Tanubrata Sutanto Fahmi Bambang and Partners which is also an international affiliated Public Accounting Firm, namely BDO International, where the financial reports of PT (Setiono et al., 2020).
Prediction of seawater salinity based on comparison of truncated spline estimators, Fourier Series and Kernel

Salinity is one of the factors that affect salt production. Salinity is defined as the level of saltiness or too much salt in water. The salt in question is a variety of ions dissolved in water, including table salt (NaCl). The higher the level of NaCl contained, the better the quality of the salt formed. This low quality causes Indonesia to import salt, both consumption salt and industrial salt. Because most of the quality of salt still does not meet the criteria of SNI. For this reason, it is necessary to predict the salinity of seawater to help determine the next steps or policies in improving the quality of salt in Indonesia, especially in the Madura area. This research is examined in the form of a nonparametric regression curve estimator with a truncated spline estimator approach, Fourier series and kernel. From the comparison results, the best model for predicting seawater salinity is the estimator of the Fourier series base sine cosine with an oscillation parameter (k) of 2 with a GCV value of 5.017987 and MSE and a coefficient of determination of 0.06299933 and 94.64373%. So the prediction results obtained in this study are close to accurate with MAPE values of 0.07225208%, MSE of 0.0001441417 and coefficient of determination of 99.99%.
A deep convolutional neural network architecture for breast mass classification using mammogram images

&lt;p&gt;Breast cancer is one of the second most common cancer occurring worldwide. Early identification of the disease is a major interest that promises to propose several diagnostic procedures to prevent further surgical interventions. This research paper aims to develop a breast mass classifier system using deep learning to differentiate breast mass images from normal mammographic images. The benchmark mammographic datasets CBIS-DDSM, INbreast, and mini-MIAS are used for constructing the proposed model DELU-BM-CNN. The region of interest is identified by applying image processing techniques (median filter, binarization and dilation) and the images are enhanced and sharpened using adaptive histogram equalization and unsharp masking techniques. The pre-processed images are trained with a minimum of five deep convolutional layers activated by an Exponential Linear Unit (ELU) which is developed from scratch for feature learning and classifying the given whole mammographic images. Dropout, Data normalization, and Global average pooling are some of the regularization techniques adopted to prevent the model from over-fitting. The proposed models are able to classify CBIS-DDSM images with an accuracy of 96.60%, INbreast images with 96.20% and MIAS images with 97.40%. The experimental results are also compared with conventional Rectified Linear Unit (ReLU) and Leaky ReLU activation function that promises the proposed model as a good prognosticator than the state-of-art models for cancer diagnosis using mammogram images as input.&lt;/p&gt;
Wavelet transform based image enhancement: A noise reduction approach

&lt;span lang="EN-US"&gt;This paper introduces a new thresholding function that mixes the soft thresholding functions and Smoothly Clipped Absolute Deviation (SCAD) for denoising images using the decimated wavelet transform technique, which is widely popular in various applications. The proposed method is applied to denoise noisy images contaminated with additive white Gaussian noise, employing the Top rule. The efficiency of this new thresholding function is also evaluated within the context of the Translation Invariant method. The results are compared with existing methods such as SCAD, soft thresholding, and the Wiener filter-based denoising approach. Parameters such as Root Mean Square Error (RMSE) and Peak Signal Noise Ratio (PSNR) are employed to assess the quality of denoising.&lt;/span&gt;
A transient survey on blockchain technology: Topology, challenges and applications

&lt;p&gt;&lt;span lang="EN-US"&gt;Recently, there has been a gigantic amount of attention that received by blockchain technology. Serving as an entrenched ledger, this technology allows a decentralized transaction. In modern life, numerous fields as applications of blockchain technology are emerging, which includes the Internet of Things (IoT), financial sector services, reputation system, and many more. Due to different properties like auditability, persistency, decentralization, and anonymity. blockchain technology serves extensively in academic and industrial sectors. Issues with security and scalability are the two main concerns that need a solution in regard to this technology. This paper represents a brief overview of blockchain technology. Furthermore, there are different challenges and advantages listed in this paper.&lt;/span&gt;&lt;/p&gt;
Effectiveness of Mussel Shells (Polymesoda erosa) as an Adsorbent to Improve Water Quality

From a quality point of view, peat water cannot be used for clean water resources, therefore it is necessary to improve the quality of peat water. An alternative effort to treat peat water can be done by adsorption process using seashell shell adsorbents. This study aims to analyze the effectiveness of mussel shells (Polymesoda erosa) as an adsorbent to improve the quality of peat water. The size of the adsorbent particles is varied, namely 8 mesh, 50 mesh, and 200 mesh. We used 30 grams of adsorbent for 300 ml water sample. The results were that the adsorbent for clam shells was able to reduce the TDS level from 402 mg/l to 112 mg/l, increase the pH level from 3.43 to 7.6 from an acidic state to an alkaline state. In this case, peat water is then suitable for use. Based on the test results, within 12 hours of contact time there was an increase in levels for all parameters along with the increase in the size of the adsorbent particles. Whereas in the contact time of 7 days, the test results experienced a decrease in levels for all parameters along with the increase in the size of the adsorbent particles which is a good optimum contact time in the adsorption process. However, the adsorbent of seashell shell has not been used effectively to adsorb turbidity and color parameters.1
A Study on Improving Digital Literacy through Redesigning of Korean Reading Classes

In this study, an online Korean reading class is suggested to improve digital literacy competence. As Korean learners are increasingly exposed to a plethora of information through digital platforms, they are experiencing a transformative shift in the dynamics of digital texts and readers within the digital space. Consequently, the cultivation of digital literacy is essential for learners to achieve communicative goals and actively engage in society. In this study, we analyze existing research on digital literacy and online reading, and categorize the essential online reading skills for Korean online reading education into the following domains: “locate online information,” “comprehend information,” “synthesize online information” “critically evaluate online information,” and “communicate online information.” The study recommends specific online comprehension strategies tailored for each stage of reading comprehension to aid in structuring of reading classes.
Enhancing User Authentication with Facial Recognition and Feature-Based Credentials

This research proposes a novel and trustworthy user authentication method that creates individualized and trusted credentials based on distinctive facial traits using facial recognition technology. The ability to easily validate user identification across various login methods is provided by this feature. The fundamental elements of this system are face recognition, feature extraction, and the hashing of characteristics to produce usernames and passwords. This method makes use of the OpenCV library, which is free software for computer vision. Additionally, it employs Hashlib for secure hashing and Image-based Deep Learning for Identification (IDLI) technology to extract facial tags. For increased security and dependability, the system mandates a maximum of ten characters for users and passwords. By imposing this restriction, the system increases its resilience by reducing any possible weaknesses in its defense. The policy also generates certificates that are neatly arranged in an Excel file for easy access and management. To improve user data and provide reliable biometric authentication, this study intends to create and implement a recognition system that incorporates cutting-edge approaches such as face feature extraction, feature hashing, and password creation. Additionally, the system has robust security features using face recognition.