Reviewerly/exHarmony huggingface dataset:
Penerapan Data Mining Pada Prediksi Harga Emas dengan Menggunakan Algoritma Regresi Linear Berganda dan ARIMA

The development of life has developed very rapidly at this time, one thing that has quite an important influence is the business processes carried out. Investment is a business that is carried out by all levels and also members of society easily and flexibly. Currently, the investment that is very popular with the public is gold. Gold itself is one of the most sought after precious metals at the moment, apart from being used to beautify oneself, gold can also be used as an investment asset. Based on several factors above, many people invest in gold. Investments made in Gold are not investments that have a short period of time but investments that are made over a fairly long period of time. Investing in Gold is done by buying Gold at a cheap price at the moment and then selling it again when the Gold price has risen. However, in the process that occurs, problems often occur, where the problems that occur are related to the price of gold. Where this problem can be solved by making a prediction. Data mining is used in predictions because the prediction process is carried out using data mining based on data processing. Data mining itself is a technique that is widely used today to assist in the problem solving process. In this research, the solution process was carried out using the Multiple Linear Regression algorithm and also ARIMA. In this research, the research process will be carried out by comparing the Multiple Linear Regression algorithm. Comparison of algorithms aims to obtain the most optimal results from implementing the algorithm. In solving using the Multiple Linear Regression algorithm and ARIMA, these two algorithms can help solve prediction problems by producing optimal results. From the process carried out, the Multiple Linear Regression algorithm has an RMSE value of 4902782.346, while the ARIMA algorithm gets a value of 5876287.332. This indicates that the results of the Multiple Linear Regression algorithm are better than the ARIMA algorithm.
Penerapan Fitur Seleksi dan Particle Swarm Optimization pada Algoritma Support Vector Machine untuk Analisis Credit Scoring

After the Covid-19 pandemic, the banking sector faced significant challenges in contributing to achieving national goals in terms of increasing living standards and equalizing the regional economy. Hundreds of millions of low-income people have no credit or bank accounts because they do not have sufficient credit history to warrant the credit scores assigned to them. An estimated 1.7 billion people (31% of the adult population) do not have an account with a financial institution. People today are usually concentrated in developing countries, especially in China 204 million, India 357 million and Indonesia 102 million people. Because it is very difficult to make accurate predictions in determining credit worthiness for low-income people. Cooperatives are financial institutions that have a crucial role in channeling financing to members and the community to develop their businesses. An inappropriate credit distribution process can have a negative effect on KSP, resulting in frequent losses. This risk is known as problem loans, the cause is the KSP's failure to analyze the credit of prospective debtors. Therefore, calculations are needed to detect opportunities for credit risk default by prospective debtors objectively and precisely so that loan problems do not occur. Credit scoring is a method used to evaluate credit risk in terms of loan applications from consumers [4]. In this research we will provide a solution using classification techniques with feature selection methods in the Particle Swarm Optimization (PSO) Algorithm and Support Vector Machine (SVM) to predict the credit risk of prospective debtors failing to make loan payments. The application of the SVM algorithm in credit scoring research is because SVM is good at data classification. However, the standard SVM model still does not produce optimal results due to the difficulty of determining the best parameters, therefore researchers will optimize it with the Feature Selection and PSO algorithms to determine the best parameters. The results from the combination of several parameters using PSO-SVM obtained an accuracy of 87.23%, therefore the application of this method was proven to improve the performance of the SVM algorithm to increase its accuracy results in predicting the feasibility of granting credit.
Analisis Dalam Pendukung Keputusan Penerimaan Supervisor Industri Manufacturing dengan Menerapkan Metode EDAS dan Pembobotan ROC

Manufacturing industry supervisor is one of the jobs engaged in processing raw goods into whole or semi-finished goods. Honest and responsible supervisors in the company are needed. Therefore, the company is opening the acceptance of supervisors who have a high responsible spirit. However, in accepting supervisors is not an easy thing because finding people who really have a high leadership spirit and are responsible is not an easy thing, therefore a system is needed that can help the company find a decision. The system is a decision support system and in finding these decisions several criteria are needed including Education, Experience, Leadership Ability, Good Interpersonal and Responsibility. And also in order to get accurate results that deserve to be supervisors can use methods where researchers use EDAS methods and ROC weighting. So in the research conducted by the author obtained the highest ranking found in alternative AD7 on behalf of Bambang with a total value of 1,00000 who was selected to be a supervisor of the manufacturing industry with complete requirements and the highest value.
Analisis Pemberian Bantuan UMKM Menggunakan Algoritma K-NN dan C4.5

The Covid-19 pandemic has had an impact on the economies of countries in the world, including Indonesia. The low trade balance, public consumption and the implementation of large-scale social restrictions (PSBB) have caused business actors to suffer losses and even go out of business, especially Micro, Small and Medium Enterprises (MSMEs). Assistance to MSMEs has been provided by the government to maintain the functioning of the economy in the micro environment. However, the provision of this assistance needs to be carried out further analysis because there are reports that the assistance is not on target, causing the budget spent to be ineffective. In this research, an analysis will be carried out on the provision of assistance from the government to MSMEs, especially in Pekalongan district, using data mining techniques, especially classification. The algorithms used are K-Nearest Neighbor (K-NN) and C.45 which are then compared to determine the highest level of effectiveness in recommendations for providing MSME assistance in the District. Pekalongan. The data used was 312 MSMEs and after going through the data preprocessing process we got accurate data, namely 279. The data was divided into 2, namely training data of 200 data and testing data of 79 data. The results of this research, the K-NN algorithm obtained an accuracy level of 94.94%, precision 94.73% and recall 94.73%, while the C.45 algorithm obtained an accuracy level of 86.08%, precision 87.21% and recall 88.3%. Based on the results of this research, it can be concluded that the use of data mining techniques with the K-NN and C4.5 algorithms has a high level of accuracy for recommendations for assistance to MSMEs, however for the best results you can use the K-NN algorithm which has an accuracy level of 94.94%.
Assessing the Effectiveness of qSOFA and SIRS Scoring Systems:t a Single-Center

In the context of post-2016 redefinitions of sepsis and septic shock, this prospective, non-interventional single-center clinical trial was carried out at St. Marina University Hospital, Varna, Bulgaria. The study encompassed 87 participants, approximately 45 of whom presented with sepsis and septic shock. Employing logistic regression, the study aimed to assess the predictive value of the Systemic Inflammatory Response Syndrome (SIRS) and quick Sequential Organ Failure Assessment (qSOFA) criteria in sepsis. Additionally, sensitivity and specificity were evaluated using ROC curve analysis. The findings revealed the substantial predictive potential of both SIRS and qSOFA for septic patient mortality. Notably, the qSOFA score exhibited a significantly higher likelihood (2.581 times, p = 0.0001, 95% CI 1.557 - 4.279) of predicting mortality compared to the SIRS scale (2.050-fold, p = 0.004, 95% CI 1.255 - 3.349). The study contributes to guiding the enhancement of patient care strategies, effortlessly aligning with the core tenets of evidence-based nursing practices.
Analisis Sentimen Aplikasi Primaku Menggunakan Algoritma Random Forest dan SMOTE untuk Mengatasi Ketidakseimbangan Data

The Primaku application is an application that can be used as a tool to monitor the growth of children under five, this application can be used to collect data on the growth of children under five, apart from that this application can also provide clear information and visualization about the growth of children under five, including nutritional status and growth development In accordance with the standards that have been set, the Primaku application can help parents or health workers in routinely monitoring the growth of children under five and early detecting the potential risk of stunting. Stunting is a growth disorder that occurs in children under five due to malnutrition which is characterized by the child's height. which is shorter than the age standard. Stunting can have a long-term impact on a child's quality of life, such as disrupting physical, cognitive and social development, as well as increasing the risk of chronic disease in adulthood. The primaku application has been widely used, more than 500,000 users have downloaded this application and 44,700 reviews have been given by users to this application, however, reading all the reviews may take time, but if there are few reviews read, then the review results will be biased. Therefore, sentiment analysis aims to overcome this problem by automatically grouping user reviews into positive and negative reviews. Therefore, research on toddler growth detection to determine the public's response to the Primaku application can be of great benefit in efforts to prevent stunting in children under five in Indonesia. In this research, the random forest algorithm with the SMOTE technique was used to carry out sentiment analysis of Primaku application reviews. The random forest algorithm is a machine learning algorithm based on decision trees. The SMOTE technique is used to overcome data imbalance problems and is able to reduce overfitting while increasing the performance of the Random Forest algorithm. The data used in this research is Primaku application review data obtained from scrapping results from the Google Play Store. This data contains comments from application users, namely positive and negative. The results of this sentiment analysis show a deep understanding of user perceptions of the Primaku application. This sentiment analysis can be a basis for further improvement and development of the Primaku application, with a focus on aspects that influence user satisfaction and the research results show that the random forest algorithm with the SMOTE technique can produce quite good accuracy in sentiment analysis of the Primaku application. obtained in this study was 88%.
Designing and Developing E-Magazine about Indonesian Cultural Concept in Social Studies Learning for Elementary School Students

The background of this research is optimizing material on cultural diversity, cultural tourism and special food in Indonesia in class IV SD in social studies learning through the digital media e-magazine Anak Bangsa. The use of the Anak Bangsa e-magazine learning media is due to the lack of use of learning media during the teaching and learning process and a decrease in love for preserving culture. This study aims to produce a product in the form of an e-magazine Anak Bangsa learning media on cultural diversity material in Social Studies class IV SD. This research uses the Design and Development method with the ADDIE model (Analysis, Design, Development, Implementation, Evaluation). The instruments used were questionnaires for validating material experts, media experts, and linguists, questionnaires for teacher and student responses, as well as interviews with educators and students. The research produced the product of Anak Bangsa e-magazine learning media with material on cultural diversity in grade IV SD. The results of the recapitulation of the feasibility test through validation by experts namely material experts, media experts, and language experts using a validation questionnaire obtained the category "Very Eligible". The results of the assessment recapitulation from the responses of educator users and students obtained the "Very Eligible" category. The learning media for the Anak Bangsa e-magazine on social studies material on cultural diversity that has been developed is suitable for use as an alternative media for learning social studies in grade IV elementary schools.Keywords: E-Magazine, Learning Media, Social Studies Learning in Elementary Schools
ANALISIS PENGGUNAAN MEDIA BIG BOOK DALAM MENGEMBANGKAN KEMAMPUAN BERBAHASA ANAK USIA 3-4 TAHUN

Language is a media for early childhood to express their feelings and experiences and communicate with others around them. This study aims to determine the impact of using big book media to develop the early childhood’s language skills aged 3-4 years. The method used in this study is a qualitative method under a descriptive approach. The results of study showed that the use of big book media empirically improve the early childhood’s language skills. The early childhood’s language skills generally develop at the level of: (1) acquiring new vocabularies, (2) fluency in pronouncing new vocabularies, (3) understanding the meaning of spoken vocabularies, and (4) being able to retell stories told by teachers based on various pictures listed in big book. In addition, the use of big book media also helps other aspects of early childhood’s development, such as: (1) cognitive aspects and (2) art aspects. In conclusion, empirically the use of big book media can help to develop the early childhood’s language skills aged 3-4 years.
CLOUD COMPUTING AND VIRTUALIZATION: CAN CLOUD COMPUTING EXIST SEPARATELY FROM VIRTUALIZATION?

Virtualization is a software technique that emulates the operation of the entire computer. Depending on the needs and the powers of the physical computer, several virtual machines can be installed at the same time. The resources of physical computers will be shared between all virtual machines and because of that, virtual machines will be working slower. A virtual machine uses a combination of software and an existing computer to provide additional computer machines, all in one physical device. Cloud computing involves delivering hosted services and cloud applications over the internet and enables users to obtain a shared pool of data from remote physical servers, databases, and computers. Although virtualization and cloud computing are seen as two different techniques, they are interconnected and cannot exist without each other. Virtualization in cloud computing can prevent the IT system from failing and can protect the IT environment from bugs and viruses. In IT infrastructure, cloud computing and virtualization are used together to build a cloud infrastructure. The aim of this study is to define and analyze what virtualization and cloud computing are. Then through a comparison to show how these techniques are related to each other and consequently a conclusion will be drawn.
ENSURING INFORMATION SECURITY IN THE DIGITAL AGE

In the digital age, information security has become increasingly important as the amount of sensitive data being stored and transmitted electronically continues to grow. Information security refers to the practice of protecting information from unauthorized access, use, disclosure, disruption, modification, or destruction. Ensuring information security in the digital age involves implementing a variety of security measures to ensure the confidentiality, integrity, and availability of information. One important aspect of information security is the protection of sensitive information, such as personal information, financial data, and trade secrets. This can be achieved through the use of encryption, secure communication protocols, and access controls. Additionally, network security is crucial in protecting information systems and networks from cyber-attacks. This can be done through the use of firewalls, intrusion detection and prevention systems, and regular security audits. Another element of information security is incident response and management, including planning for and responding to security breaches. This can involve activating incident response teams, conducting forensic investigations, and implementing recovery plans to restore normal operations. A comprehensive information security program also includes employee education and awareness, security policy, and compliance with relevant regulations and standards such as PCI-DSS, HIPAA, and ISO 27001. Overall, information security is a constantly evolving field as new technologies and attack methods are developed. It requires ongoing monitoring, testing, and updating of security measures to ensure the ongoing protection of information in the digital age.
СИСТЕМЫ СВЯЗИ СПЕЦИАЛЬНОГО НАЗНАЧЕНИЯ

The article discusses the principles of human-machine control communication systems for special purposes, which belong to the class of controlled systems. In addition, the authors' attention is drawn to the methodological principles of the study of such systems; the functional architecture of a special purpose communication system (SPCS) in the form of a three-level conceptual model is considered. The most general methodological principles of communication system research, considered in the work is a systematic approach. Within the framework of this approach, an interconnected special-purpose communication system is considered as an integral part of the control system of higher-order systems. The authors believe that the methodology of the study of such systems is mainly based on a combination of methods of induction (from particular to complex) and deduction (decomposition), that is, consideration from general to particular, from simple to complex. The hierarchy of the SPCS description is used as a method of eliminating contradictions between simplicity and taking into account the remaining multiple parameters of the system. Each level of the hierarchy corresponds to specific features, functions, laws and principles, terms and concepts, using which it is best possible to predict and describe the functioning of the SPCS.
ПРОЕКТИРОВАНИЕ И РАЗРАБОТКА ИНТЕГРИРОВАННОГО МОБИЛЬНОГО ПРИЛОЖЕНИЯ, ОБЪЕДИНЯЮЩЕГО ВОЗМОЖНОСТИ 2ГИС, ZENLY И GOOGLE MAPS

This article focuses on creating a universal mobile application that combines the power of 2GIS, Zenly and Google Maps to optimize user navigation and improve the location experience. This innovative application integrates the strengths of these platforms, simplifying navigation, route planning, real-time tracking of public transport and promoting social connectivity. The study covers the design, implementation and evaluation of this innovative solution, highlighting its potential to revolutionize modern location services. The main goal of the project is to create and evaluate a comprehensive mobile application that provides users with a single tool for location services, integrating the core functions of 2GIS, Zenly and Google Maps. The app's design pays attention to usability, using detailed Google Maps for accurate and up-todate location information. In summary, this study represents a significant contribution to the field of mobile navigation applications, demonstrating the potential to transform modern location services.
СИСТЕМА ГОЛОСОВАНИЯ НА ОСНОВЕ БЛОКЧЕЙНА: СИСТЕМАТИЧЕСКИЙ ОБЗОР ЛИТЕРАТУРЫ

Democratic elections are a cornerstone of modern society, enabling citizens to exercise their right to vote and express their preferences for political leaders and policies. However, traditional voting systems have faced numerous challenges in recent years, including allegations of fraud, hacking, and misinformation. To address these challenges, many countries have started exploring new technologies that can help secure and modernize the voting process. One such technology is blockchain, a decentralized and tamper-proof database that allows multiple parties to maintain a shared ledger without the need for a central authority. By providing a transparent and immutable record of all transactions, blockchain technology has the potential to revolutionize the way we conduct elections, making them more secure, transparent, and efficient. In this paper, we will explore the benefits and challenges of using blockchain technology in voting systems.
Reading Proficiency Levels in English among the Intermediate Graders in Manito District SY 2022-2023

This study aimed to determine the reading proficiency levels in English among intermediate graders in the Manito District, as well as the factors that affect these levels. The research design utilized for this study is descriptive-correlational, which describes the relationship between the responses of English teachers and the school reading coordinators on the factors affecting the reading proficiency levels in English among intermediate graders. The four categories of factors that were explored in this study were pupil factors, teacher factors, home factors, and curriculum factors. The research findings indicated that pupil factors such as vocabulary, comprehension, and word recognition impact intermediate graders' reading proficiency levels in English. Home factors such as parental involvement, access to reading materials, and socioeconomic status also contribute to the development of reading proficiency. Teacher and curriculum factors had no significant relationship with reading proficiency levels in English. By addressing the identified factors, parents can be provided with support, and pupils can be given reading materials to create a home learning environment that promotes literacy development. A contextualized illustrated short stories and workbook as supplementary reading material was developed to improve reading proficiency levels in English among intermediate pupils.
Implementasi Metode EDAS Dalam Penilaian Kinerja Dosen Pada Masa Pandemi Covid-19 dengan Pembobotan Entropy

Along with the development of technology that makes online learning run well, but the enthusiasm for student learning is not like when face to face and there are still many students who do not take various courses so that students' knowledge abilities are greatly decreased. When online learning takes place, it is very necessary for a lecturer's performance to arouse students' enthusiasm in participating in online learning. Because during this pandemic the role of lecturers is very necessary to develop an innovation and be able to make students not bored in participating in online learning. And also in terms of the performance appraisal process, several problems often occur, namely the speed in the performance appraisal process and also the accuracy of the performance appraisal. In assessing the performance of lecturers during online learning, there are several criteria including Discipline, Delivery of Materials, Interaction, Discussion Questions and Answers and Punctuality. Based on these problems, a decision support system is needed as a problem solving technique and is assisted by a method that can produce an accurate final value. The method is the Evaluation Based On Distance From Average Solution (EDAS) and Entropy method which is very helpful in generating weight values ??from alternative data and criteria so as to get the final results obtained in Alternative L9 with a value of 0.31025 on behalf of Surya Darma Nst, M. Kom.