bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Distributed Graphs for Facilitation of Scalable Botnet Detection and Response
Authors: Atti Mangadevi , Kumar Yogi Manas
Published: March 2024

Botnets pose a significant threat to modern network environments, exploiting compromised devices to carry out malicious activities such as distributed denial-of-service attacks, spam campaigns, and data theft. Traditional centralized detection systems often struggle to handle the scale and complexity of botnet attacks, leading to delays in detection and response. In response to these challenges, this paper explores the application of distributed graphs for facilitating scalable botnet detection and response. Distributed graphs offer a promising approach for modelling and analyzing complex network structures, enabling efficient detection of botnet propagation patterns and anomalous behaviour across distributed computing environments. The paper presents an overview of distributed graph-based botnet detection systems, discussing their architecture, design considerations, and key concepts such as graph partitioning, vertex-centric computation, and message passing in distributed graph algorithms. Case studies illustrate the practical application of distributed graph-based botnet detection in diverse network environments, highlighting success stories, challenges encountered, and lessons learned from deploying distributed graph systems in production cybersecurity operations. Finally, the paper discusses challenges and open research questions in the field of distributed graph-based botnet detection, addressing issues such as graph partitioning strategies, fault tolerance, privacy-preserving techniques, and integration with other security tools. It proposes potential avenues for future research and development in scalable botnet detection using distributed graphs, emphasizing the importance of adaptive threat response, collaboration with industry partners, and continuous improvement in detection algorithms for enhancing cybersecurity resilience against botnet attacks.
Principais intercorrências na estética com o uso do ácido hialurônico
Authors: Maria Pereira Dos Santos Rebeca , Beatriz Pereira Lima Ana , Da Mata Morales Bonifácio Larissa , Ferrazzini Lozano Valquíria
Published: March 2024

Considerando o aumento da procura por procedimentos estéticos pela população em geral, tem crescido exponencialmente os estudos relacionados a esses procedimentos, técnicas e produtos utilizados para satisfazer esse anseio social. Essa ascensão impacta diretamente a área biomédica e os profissionais ligados a esta ciência. Assim, partindo desse pressuposto e diante da vasta necessidade de conhecimento aprofundado em razão da ligação direta à saúde e bem-estar das pessoas, busca-se aprofundar os estudos das principais intercorrências da aplicação do ácido hialurônico como preenchedor facial. Para tanto, na elaboração deste trabalho foi realizado um levantamento bibliográfico com foco na abordagem dos efeitos adversos decorrentes da aplicação do ácido hialurônico como procedimento estético. Sobretudo, quanto aos riscos decorrentes desses procedimentos, em especial, do ácido hialurônico aplicado na face e servir como alerta das consequências desfavoráveis decorrentes da aplicação, tanto aquelas conhecidas pela ciência quanto aquelas que ainda necessitam de estudos mais aprofundados, ainda com a indicação de possíveis tratamentos que possam mitigar a ocorrência  e/ou consequência de tais intercorrências e, sendo elas inevitáveis, apresentar caminhos já conhecidos pela ciência para reparação das consequências decorrentes de tal aplicação. Essa pesquisa, mostra que é recorrente a utilização de ácido hialurônico como preenchedor facial. E, ainda, embora sejam remotas, existem diversas intercorrências oriundas da aplicação de AH, umas mais gravosas e outras mais amenas, que merecem atenção e qualificação especializada do profissional que utilizar este método. Conclui-se que, embora exista no mercado tratamentos que possam reverter algumas intercorrências, é imprescindível a capacidade técnica do profissional especializado para realização do procedimento estético em que se utiliza o ácido hialurônico como preenchedor, em razão da observância nos mais diversos espectros que podem influenciar tanto no procedimento, quanto com relação ao paciente.
Toolkit for creating a safety culture for future railway workers
Authors: Merezhnikova M. A.
Published: March 2024

JSC ‟Russian Railways” is carrying out comprehensive work to reduce injuries to zero, including by increasing the level of professional training of employees. Safety culture as a derivative of the international movement Vision Zero, has become an important part of the occupational safety management system in Russian Railways and has radically changed the approach to the identiﬁcation and prevention of injuries in railway transport. Students of transport technical schools and universities should join the Vision Zero international movement at the stage of education, that is, much earlier than the actual start of work. To do this, it is proposed to introduce a system of annual labor protection months in educational institutions, which will become the basis for the formation of a safety culture. Conducting such months gives the student the opportunity to take part in them for several years in a row, at the beginning of training to a greater extent as a listener and spectator, but at senior courses, to act as a lecturer, organizer and participate in more signiﬁcant events.

Constant work on the formation of a ‟correct” understanding of the importance of compliance with the safety standards and rules of future railway workers will become the basis for the eradication of injuries due to unfair compliance with the requirements of labor protection instructions.
Analysis of Currents in Open Water Southwest of Lae Lae Island
Authors: Said Irwan Anwar , Sugianto Denny Nugroho , Zainuri Muhammad , Syamsudin Nur Taufik , Jalil Abdul Rasyid , Ibrahim Ibrahim
Published: March 2024

Ocean currents are one of the movements of horizontal or vertical mass movement of seawater that takes place continuously.  The purpose of this study is to determine current conditions in open water close to narrow strait waters, as well as canal estuaries.  Current data is the result of measurements that have been carried out using ADCP (Acoustic Doppler Current Profiler) mini type ADP-SONTEK equipment on May 16, 2018, while tidal data refers to the recording results of the Makassar BIG tidal station.  The results showed that the total surface current speed ranged from 0.017 – 0.375 m/sec with a dominant direction to the west or to open water both at high tide and at low tide.  While the result of separation, the speed of tidal currents ranges from 0.032 – 0.343 m / sec.
Formulation and Stability of Microemulsion Preparations From Secang Wood Extract (Caesalpinia Sappan L) and Virgin Coconut Oil (VCO)
Authors: Setyopratiwi Ani , Rahman Fathru Naban , Prasetyo Niko
Published: March 2024

Research has been conducted to make microemulsion preparations from virgin coconut oil (VCO) and secang wood extract. The purpose of this study was to determine the characteristics of secang wood extract with ethanol solvent, determine the Hydrophilic Lipophilic Balance (HLB) value of a mixture of three surfactants that can form the most stable microemulsion preparations, and determine the most optimal variation in the concentration of secang wood extract in secang microemulsion formulations.This study began with the manufacture of secang wood ethanol extract from secang wood powder and 96% ethanol, then tested for flavonoid levels. Furthermore, VCO microemulsions in a mixture of water with secang extract are made with variations in HLB values, namely 12, 13, 14, and 15. Microemulsions with HLB variations were tested for stability through organoleptical observations and turbidity values by storage treatment at room temperature, heating, and centrifugation. Microemulsions were also tested for free fatty acid (FFA) levels. After that, the preparation of microemulsions with the most stable HLB is carried out with variations in the concentration of secang wood extract in the formulation. Microemulsions with extract variations were tested for stability through organoleptical observation and turbidity values after 24 hours, heating, and centrifugation. Microemulsions with optimal concentrations of secang wood extract were tested for antioxidant activity. The secang extract produced from the extraction was reddish-brown in color and had total flavonoids equivalent to 230.6 mg QE/g samples. The most stable microemulsion from this study is a microemulsion with an HLB value of 15 with a ratio of water:extract:VCO:surfactant which is 65:2,5:2,5:30. The microemulsion features transparent red, 1 phase, and smells like Tween 80 with turbidity value below 1% during storage, heating, and centrifugation with microemulsion FFA value of 0.53%. Based on variations in the concentration of secang wood extract, the higher the concentration of the extract, the more unstable the microemulsion produced. The 3% secang extract microemulsion is the most optimal microemulsion with antioxidant activity (IC50) of 1.4573±0.2694 mg/mL.
Penerapan Metode Simple Additive Weighting dalam Penentuan Prioritas Program Pembangunan Daerah
Authors: Siagian Jaya Sari Anggraini , Purba Bister , Ambarsari Erlin Windia , Rohayani Hetty
Published: March 2024

Regional governments and institutions related to preparing regional development programs experience several obstacles in determining regional development work plans, one of which is difficulty in determining development priorities that are in line with regional regulations. The effectiveness and efficiency of implementing regional development programs depends on the accuracy of the data collected. One of the challenges faced by the Medan City Regional Development Planning Agency is the lack of consideration of the priority scale and fairness in the regional development stages, as well as the absence of a system that can help determine the priority scale. Therefore, this research requires a decision support system (DSS). In the SPK, there are many solution methods that can be used according to the needs of each problem. In this research, to determine regional development program priorities, the SAW method will be used. Of the 10 proposed regional programs, only one will be a priority development program. After applying the SAW method in making decisions, the development program that has the highest priority level is the highway construction program with the final result obtained, namely 0.77705.
Implementasi Metode EDAS Dalam Penilaian Kinerja Dosen Pada Masa Pandemi Covid-19 dengan Pembobotan Entropy
Authors: Indini Dwina Pri , Siregar Tesa Aurelia , Utomo Dito Putro
Published: March 2024

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.
Analisis Pemberian Bantuan UMKM Menggunakan Algoritma K-NN dan C4.5
Authors: Suseno Akrim Teguh , Amin M Al , Mahardika Fajar
Published: March 2024

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%.
Penerapan Fitur Seleksi dan Particle Swarm Optimization pada Algoritma Support Vector Machine untuk Analisis Credit Scoring
Authors: Naufal Abdul Razak , Suseno Akrim Teguh
Published: March 2024

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.
Data Mining Perbandingan Algoritma K-Nearest Neighbor dan Naïve Bayes dalam Prediksi Penerimaan Beasiswa
Authors: Kushartanto Ahmad Ilham , Aldisa Rima Tamara
Published: March 2024

One of the goals of the Indonesian State as stated in the Constitution of the Republic of Indonesia is to make the nation's life more intelligent. The government, through the Ministry of Education, Culture, Research and Technology (Kemendikbudristek), is implementing a 12-year compulsory education program. The Indonesia Smart College Card program will start to be implemented in 2021, where initially this program was called bidikmisi. The Indonesia Smart College Card program is intended to help children who experience economic difficulties or are constrained by the costs of continuing their education at tertiary level. Beneficiaries of the Indonesian Smart College Card program will receive full tuition fees from the start of admission to completion of the course within the agreed time period. This aims to ensure that children who have been selected to become students no longer have to worry or feel afraid about their survival when studying. Placing limits on the number of recipients of the Indonesia Smart Tuition Card for Private Universities (PTS) is a problem that must be resolved properly and carefully. The selection process for prospective students who register at the target university aims to find recipients who are worthy of assistance from the Indonesia Smart College Card program. The selection process for prospective students who register at the target university aims to find recipients who are worthy of assistance from the Indonesia Smart College Card program. The results obtained from the application of the research were that from comparing the results of the K-NN and Naive Bayes algorithms, the same results were obtained for the test data, namely Acceptable.
Sistem Pakar Diagnosa Penyakit Angsa Menggunakan Metode Forward Chaining Berbasis Web
Authors: Guko William Yviis , Eviyanti Ade , Hindarto Hindarto
Published: March 2024

Geese have many benefits for human needs. Starting from meat, eggs, feathers, fat, and other uniqueness such as guarding other livestock if there are animals or strangers approaching their territory. However, in Indonesia, goose utilization is less desirable and only a few do it. This poses a probӏem for goose breeders due to the absence of knowӏedge about the diseases experienced and the handӏing soӏutions. An expert system is an artificiaӏ inteӏӏigence that supports expert decision-making. The forward chaining method provides conclusions through rules derived from existing facts. This Expert System for Diagnosing Swan Diseases Using the Web-Based Forward Chaining Method is designed to make it easier for farmers or users to consult about the diseases experienced and treatment solutions with 90% diagnostic results. This expert system is made based on a website that can be accessed easily and at any time. Based on black box testing, the results obtained show 100% system functionality, so this expert system application can be used.
Prediksi Harga Kelapa Sawit Menggunakan Metode Extreme Learning Machine
Authors: Hariansyah Jul , Budianita Elvia , Jasril Jasril , Afrianty Iis
Published: March 2024

Palm oil is one of the keys to the Indonesian economy and the main commodity for attracting foreign investment. The palm oil and palm kernel industry generates most of the foreign currency from palm oil. The price of palm oil often goes up and down every month resulting in instability in the income received by people who own oil palm plantations. The aim of predicting palm oil prices is to carry out appropriate planning or steps for palm oil business actors. One way to overcome this problem is to make predictions. One method that can make predictions is the Extreme Learning Machine (ELM). ELM is an artificial neural network method used to predict palm oil prices. The ELM method is a feedforward method with a single hidden layer which is better known as a single hidden layer feedforward neural network (SLFNs). In this research, the best implementation was 5 inputs with 20 neurons in the hidden layer with output in the form of palm oil price predictions. Based on the tests carried out, the research produced the smallest error rate of 0.0027111424247658633 using 20 neurons in the hidden layer so that the latest data prediction test results for 5 price rotations in September rotation 1 were 1400.314191, September rotation 2 were 1846.798921, September rotation 3 amounted to 1505.430419, September rotation 4 amounted to 2301.853412, September rotation 5 amounted to 2645.082489 in palm oil price predictions.
Sentiment Classification of Over-Tourism Issues in Responsible Tourism Content using Naïve Bayes Classifier
Authors: Afrianto Singgalen Yerik
Published: March 2024

The research problem addressed in this study is the analysis of public sentiment regarding over-tourism issues. Utilizing the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology and the Naive Bayes Classifier (NBC) algorithm, the study navigates through stages of business understanding, data processing, modeling, evaluation, and deployment. The central focus lies in understanding and classifying public sentiments surrounding the challenges associated with over-tourism. The findings reveal that the NBC algorithm, particularly when augmented with Synthetic Minority Over-sampling Technique (SMOTE), demonstrates superior performance metrics, showcasing an accuracy of 84.82%, precision of 91.69%, recall of 76.75%, f-measure of 83.47%, and AUC of 0.838. The comparison with NBC without SMOTE, which registers an accuracy of 78.16%, precision of 87.61%, recall of 74.56%, f-measure of 80.51%, and AUC of 0.745, underscores the significance of addressing class imbalance for improved predictive performance. Integrating CRISP-DM with the NBC algorithm and SMOTE proves instrumental in advancing sentiment analysis methodologies, providing nuanced insights into public perceptions and attitudes concerning the critical issue of over-tourism.
Sentiment Classification of Robot Hotel Content using NBC and SVM Algorithm
Authors: Singgalen Yerik Afrianto
Published: March 2024

Sentiment analysis plays a pivotal role in comprehending public sentiment, notably within digital communication, where copious amounts of textual data are generated daily. This study delves into the efficacy of sentiment classification models, namely the Naive Bayes Classifier (NBC) and Support Vector Machine (SVM), within the imbalanced datasets commonly encountered in sentiment analysis tasks. Employing a comparative analysis methodology, a dataset comprising robot hotel reviews from online platforms is the basis for evaluation. Both NBC and SVM models undergo training and assessment, with and without the Synthetic Minority Over-sampling Technique (SMOTE), to rectify the class imbalance. Performance evaluation relies on critical metrics, including accuracy, recall, precision, f-measure, and Area Under Curve (AUC) to gauge model effectiveness. Findings demonstrate SVM's superiority over NBC in terms of accuracy (SVM: 76.88%, NBC: 67.43%), precision (SVM: 92.03%, NBC: 86.87%), recall (SVM: 58.88%, NBC: 41.00%), f-measure (SVM: 71.78%, NBC: 55.63%), and AUC (SVM: 0.907, NBC: 0.961). Incorporating SMOTE significantly enhances both models' performance, particularly in addressing class imbalance concerns. Although NBC exhibits a more balanced performance across precision and recall metrics, SVM demonstrates heightened accuracy and predictive capability in sentiment classification tasks. These findings underscore the pivotal role of algorithm selection and preprocessing techniques in optimizing sentiment analysis performance, thereby providing invaluable insights for practitioners and researchers alike.
Sistem Pakar Pemilihan Bibit Padi Unggul dengan Metode Forward Chaining
Authors: Efan Efan , Sasmita Sasmita , Suhada Desmi Aulia
Published: March 2024

Expert systems are technologies that are widely used in the agricultural sector, one of which is for selecting seeds. Rice is one of the most important food crops in life, rice is the main source of carbohydrates for the majority of the world's population. One of the important factors influencing the growth of rice production is better and better quality seed so that it can increase the productivity of rice plants, using better seed can increase yields up to three times a year. This research aims to develop an efficient system for selecting superior payi seeds using the Forward Chaining method, in order to assist the mappers in selecting payi seeds that are in accordance with their criteria. This research was motivated by the process of selecting rice seeds by farmers who still had little knowledge about rice and was carried out by asking people who only understood rice.  The system development method uses the Waiter Faill method, which Taihaipain uses, including analysis, design, coding and testing, uses the system using Axure applications, StarUML for development, Visual Studio Code applications for coding, PHP, HTML for programming skills, and Database XAMPP and MySQL. The testing method uses the Blackbox Testing method, namely to determine whether the functionality, input and output of the software meets the required specifications. The results of the research show that all application features function well after being tested using the black box testing method. This expert system also helps the community in choosing rice seeds, as shown through interviews that 85% of respondents need this system.
Analisis Kombinasi Algoritma K-Means Clustering dan TOPSIS Untuk Menentukan Pendekatan Strategi Marketing Berdasarkan Background Target Audiens
Authors: Ngaeni Nurus Sarifatul , Kusrini Kusrini , Kusnawi Kusnawi
Published: March 2024

The promotion is an annual agenda for STIMIK Tunas Bangsa Banjarnegara. The aim of this promotional activity is to attract more new students every year. On the other hand, campus promotion encounters obstacles in mapping applicant data from previous years so that considerations for new promotion policies are based on data from the school of origin of alumni or students. By using the K-Means Clustering algorithm, applicant data can be grouped according to the background represented through the school origin attribute. , parents' occupation and place of origin. Then the data is processed using DSS with the TOPSIS method to obtain priority references for marketing types for each cluster. The results of calculating the silhouette coefficient value for the five clusters obtained a score of 0.426. Meanwhile, in the ranking process using the TOPSIS method, the first rank was found in cluster 0 with a score of 0.994110. Further stages use the Decision Tree method to obtain output in the form of recommendations for promotion types for each cluster. For example, cluster 0 is recommended to use promotion types with codes P1, P2, P3, P8 and P9.
Penerapan Sistem Pendukung Keputusan Pada Pengambilan Keputusan Penilaian Kinerja Karyawan dengan Menerapkan Metode MOOSRA
Authors: Utomo Dito Putro
Published: March 2024

The quality of the company will increase as employee performance increases. There are many ways that companies or organizations can improve employee performance. One way is to provide awards or rewards for employees who excel and for employees who are not able to provide their best performance, they will be given as a consequence. Rewards will be given by assessing employee performance. So far, Kofipindo has only relied on leaders' decisions to assess employee performance. This makes employees less motivated to show their best performance. Decision support systems are alternative solutions or alternative means and steps to resolve problems so that problems can be resolved effectively and efficiently. The Moosra method is used to calculate the weight of the criteria and determine the level of rejection as the main criterion. Where the decision support system is used as a model or reference in the decision-making process, especially in the employee performance assessment process. The Moosra method examines the suitability of separating a set of alternative value data with certain criteria described in the decision matrix. The aim of the research is to assist in the employee performance assessment process, making it easier for companies to provide rewards for the performance results of selected employees. The results obtained in the research process were Alternative (A10) with the name Roland Zebua as the employee with the best performance assessment.
ANALISIS STRATEGI E-COMMERCE PADA PT. SPADA INOVASI DIGITAL MENGGUNAKAN METODE IT BALANCED SCORECARD
Authors: Abdullah Muhammad , Widarto Nabilla Umniyah , Zuhdi Rafi , Puspitaningrum Ari Cahaya , Fitriani Laqma Dica
Published: March 2024

The use of information systems is one of the IS/IT investments in a company. Information systems can certainly improve company performance, but many information systems have not been implemented optimally, and do not meet the company's vision, mission and goals. This research was conducted with the aim of making strategic planning for the implementation of the E-Commerce information system at PT. Beware of Digital Innovation. The strategic plan was developed based on the IT Balanced method. Data collection was carried out through interviews, then the data obtained was subjected to SWOT analysis, then mapped into the IT Balanced Scorecard. This research produces strategic recommendations that companies can implement, including: 1) from an operational excellence perspective, companies need to determine IS/IT employees and regular maintenance; 2) user orientation perspective, companies need to adjust the interface design according to customer wishes and provider manuals as a template for system use; 3) future orientation perspective, companies need to recruit employees which can be done with background checks; 4) from a business contribution perspective, companies need to maintain and improve service quality. It is hoped that the results of this research can improve the quality of PT Waspada Innovation Digital's e-commerce.
SISTEM PENYIRAMAN DAN PEMUPUKAN OTOMATIS BERBASIS INTERNET OF THINGS (IOT) DENGAN PEMANTAUAN ANTARMUKA APLIKASI ANDROID
Authors: Wiranto Wiranto , Musyrifah Musyrifah , Mansyur Muh Fuad
Published: March 2024

Technological developments in the field of agriculture are now expanding widely, various modern tools must be owned to assist farmers in cultivating plants. The owners of the chili plants do watering and fertilizing by collecting water or fertilizer and then giving it to the plants one by one. This is not a problem if the plant owner has free time. However, if the plant owner is busy with other things or is having business that makes the plant owner unable to care for the plant, then this becomes a problem because when the plant does not receive sufficient care, the plant will easily wither and die. Seeing the existing problems, this research will design a system that can automatically water and fertilize plants based on IoT with monitoring from an Android application. The design of this system uses an Arduino microcontroller as a controller, the nodeMCU esp2688 wifi module to send data from the sensor to the web server, a soil moisture sensor to determine soil moisture, a real time clock (RTC) for fertilization scheduling and a relay as an automatic switch on the water pump. This system aims to help the activities of farmers who still use physical force to water and fertilize plants. The IoT-based automatic watering and fertilizing system uses the prototype development method, namely by collecting system requirements, building prototyping, evaluating prototyping, coding the system, testing the system, evaluating the system and using the system
ANALISIS PERBANDINGAN METODE ARIMA DAN LEAST SQUARE UNTUK PREDIKSI HARGA EMAS : PENDEKATAN PROBABILISTIK DAN STATISTIK
Authors: Anggelia Dita , Riti Yosefina Finsensia , Siswanto Paulus William
Published: March 2024

Gold, a precious metal renowned for its value in various sectors, including investment and jewelry, is often considered a secure asset within investment portfolios. However, its prices exhibit high volatility influenced by economic, geopolitical, and global financial factors. Previous research has focused on predictive methods to anticipate gold price movements. In recent years, heightened complexity and uncertainty, exacerbated by global factors such as economic shifts and the Covid-19 pandemic, emphasizes the urgency of accurate gold price predictions. This study comprehensively analyzes and compares the performance of Autoregressive Integrated Moving Average (ARIMA) and Ordinary Least Squares (OLS) in forecasting gold prices, utilizing statistical and probabilistic approaches. ARIMA excels in handling time series data, identifying complex patterns, and forecasting price changes based on historical trends. Conversely, OLS, a probabilistic method, stands out in adjusting linear models to gold price data, providing detailed insights into influencing factors. The research employs a 5-year gold price dataset (2018-2023) and evaluates the models' performance using Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). Results indicate OLS outperforms ARIMA, with lower MSE (45.79 vs. 284.83) and MAPE (0.0026 vs. 0.0066). This study contributes nuanced insights for market participants, investors, and researchers to comprehend commodity market behaviour, particularly in gold, emphasizing the importance of accurate prediction methods in strategic decision-making.
COMMUNITY SERVICE APPLICATIONS FOR VILLAGE OFFICE USING LARAVEL FRAMEWORK
Authors: Nuryani Ely , Hasanah Huswatun , Oktavani Nicko , Ruhiawati Irma Yunita
Published: March 2024

The government has developed a population administration system to support public services, one of the media used by the government is electronic government (e-government). One of the villages that has a large Regional Revenue and Expenditure Budget (APBD) in the Serang district, Banten province is Ranjeng village, Ciruas sub-district. The problem is that data management in villages is still carried out semi-manually, there is no specific application to handle this management so it is not time efficient, reporting and the level of service to the community is less than optimal. To overcome these problems, a system is needed that can help the community in submitting letters and can help the village government to improve services to the community. The system design used in this research is using the Waterfall method so that it is easier to develop and using UML (Unified Modelling Language) for visual system modelling, while the programming language used is PHP using the Laravel framework. The final result of this research is a system that can improve the services of the Ranjeng Village Office to the community to be optimal.
Asia Africa's Impact on Middle East's Specialty Coffee Community
Authors: Maspul Kurniawan Arif
Published: March 2024

In an era when work entails accomplishment, personal progress, financial security, social connections, and finding meaning, the specialty coffee sector has become a magnet for experts from Asia and Africa looking to offer their skills to the Middle East's coffee value chain. This engrossing study dives into the motivations and preferences of labor from different regions, offering light on the unique dynamics that entice people to this particular sector and geographical context. The article investigates the cultural interchange, skill development opportunities, and career progression that attract workers to the Middle East's specialty coffee industry using prominent ideas such as the Pull-Push Theory, Resource-Based View Theory, and Cultural Diversity Theory. The findings not only demonstrate the transforming potential of work, but they also give critical insights for industry stakeholders, governments, and scholars interested in maintaining a thriving and inclusive coffee ecosystem in the region and beyond.
A Formação didático-pedagógica do docente de matemática
Authors: Santos Douglas Manoel Antonio de Abreu Pestana dos
Published: March 2024

Este artigo aborda a formação didático-pedagógica de futuros professores de Matemática através de uma perspectiva descritiva exploratória, destacando a relevância das disciplinas específicas e pedagógicas independentemente do método de ensino. Considera-se que as recentes mudanças na Educação Básica no Brasil trazem desafios significativos, como a necessidade de uma compreensão aprimorada sobre o aluno, o próprio papel do educador e novas abordagens de ensino e avaliação. Tais mudanças demandam uma reavaliação dos conceitos e procedimentos matemáticos tradicionais, visando uma compreensão crítica e contextualizada da Matemática como prática social. O artigo argumenta que o atual cenário educacional exige dos professores competências que não estão sendo suficientemente desenvolvidas em sua formação, apontando para a importância de uma base teórica e prática que atenda às necessidades do conhecimento profissional na área de Educação Matemática.
Teoria do conhecimento de Paulo Freire: Aplicação de uma Sequência Didática no Ensino de Ciências
Authors: Almeida Andeson de Oliveira , Valente Natália Parente de Lima , Abreu Maria do Socorro Cardoso de
Published: March 2024

Essa pesquisa configura-se como um estudo de caso que tem como objetivo desenvolver e analisar a aplicação de uma sequência didática fundamentada na teoria de conhecimento de Paulo Freire na disciplina de Ciências em uma turma do 9° ano do Ensino Fundamental, de uma escola pública situada em Fortaleza/Ceará. Os dados foram obtidos por meio da análise de questionários semiestruturados, aplicados de forma online, de modo que os alunos apresentassem seus conhecimentos sobre a importância e os impactos da química na sociedade e em suas vidas, e os conceitos de propriedades e transformações da matéria. Os resultados apontam que a sequência didática desenvolvida proporcionou um ambiente de reflexões críticas do contexto social do aluno, contribuindo para a sua formação e estimulando o pensamento crítico sobre a papel da Química para o desenvolvimento da sociedade.
Some aspects of the development of regional agro-cluster structures as promising areas for the development of cooperation
Authors: Санду И.С. , Буторин С.Н.
Published: March 2024

В статье показана роль кооперации как ключевого аспекта развития региональных агрокластерных структур в такой области, как научно-техническое развитие сельского хозяйства, служащего основой комплексного развития сельских территорий. Показано, что кооперация на принципах инновативности и инновационности является условием научно-технического развития селькохозяйственного производства до уровня, именуемого «высокотехнологический». На примере картофелеводства в Пермском крае обоснована необходимость кооперации участников сельхозпроизводства со стороны как науки, так и практики через региональные агрокластерные структуры на принципах инновационности и инновативности.

The article shows the role of cooperation as a key aspect of the development of regional agro-cluster structures in such an area as scientific and technical development of agriculture, which serves as the basis for the integrated development of rural areas. It is shown that cooperation based on the principles of innovativeness and innovativeness is a condition for the scientific and technical development of agricultural production to the level called “high-tech”. Using the example of potato growing in the Perm Region, the need for cooperation of agricultural production participants from both science and directly from agricultural producers “on the ground” through regional agro-cluster structures based on the principles of innovation and innovativeness is substantiated.
Hybrid machine learning models for financial market analysis
Authors: Буханец А.К. , Дудник Д.А. , Косникова О.В.
Published: March 2024

В статье дается обзор исследовательской деятельности в сфере, связанной с гибридными моделями машинного обучения, которые применяются при анализе финансового рынка. Рассматриваются инновационные подходы, которые позволяют совмещать достоинства того или иного метода в обучении с точным прогнозированием и осуществлением управленческих решений на практике, с учетом сложности среды, где функционируют финансовые рынки.

The article provides an overview of research activities in the field related to hybrid machine learning models that are used in financial market analysis. Innovative approaches are considered that allow combining the advantages of a particular method in training with accurate forecasting and implementation of management decisions in practice, taking into account the complexity of the environment where financial markets operate.
Corruption analysis through mathematical methods of graph theory
Authors: Лобас Е.Р. , Канфора Д. , Руднев С.Г. , Ковалева К.А.
Published: March 2024

Статья посвящена применению графовой теории в моделировании коррупционных схем. Графовая теория предоставляет ценные инструменты для анализа сложных взаимосвязей между участниками коррупционных действий. Исследование направлено на изучение потенциала данной теории для выявления и анализа структуры и динамики коррупционных отношений. Предлагается методология построения графов коррупционных сетей и анализа их характеристик, что позволяет углубить понимание механизмов функционирования и распространения коррупции в социально-экономических и политических системах.

The article is devoted to the application of graph theory in modeling corruption schemes. Graph theory, which is a branch of mathematics that studies the properties of graphs, provides valuable tools for analyzing complex relationships between participants in corrupt actions. The research is aimed at exploring the potential of graph theory to identify and analyze the structure and dynamics of corruption relations. A methodology for constructing graphs of corruption networks and analyzing their characteristics is proposed, which allows to deepen understanding of the mechanisms of functioning and spread of corruption in socio-economic and political systems.
The theory of queuing in the management of urban transport systems
Authors: Хвостова Е.А. , Андрусенко Ю.А. , Драгуленко В.В. , Ковалева К.А.
Published: March 2024

В статье дается анализ применения теории массового обслуживания в контексте управления городскими транспортными системами. Работа фокусируется на изучении влияния теории массового обслуживания на эффективность и функциональность городской транспортной инфраструктуры. Теория массового обслуживания, представляющая собой комплексный математический аппарат для описания и анализа систем массового обслуживания, где субъекты (клиенты) обращаются за получением определенных услуг, занимает центральное место. В контексте городских транспортных систем эти субъекты выступают в роли пассажиров, ожидающих обслуживание на остановках и перемещающихся с помощью транспортных средств. Исследование представляет собой значительный вклад в разработку и реализацию инновационных подходов к управлению городскими транспортными системами на основе принципов теории массового обслуживания, что имеет ключевое значение для повышения эффективности и устойчивости городской транспортной инфраструктуры в условиях быстро меняющегося городского ландшафта.

The article analyzes the application of queuing theory in the context of urban transport system management. The work focuses on the study of the impact of queuing theory on the efficiency and functionality of urban transport infrastructure. The theory of queuing, which is a complex mathematical apparatus for describing and analyzing queuing systems where subjects (customers) apply for certain services, occupies a central place in our study. In the context of urban transport systems, these actors act as passengers waiting for service at stops and moving by means of vehicles. The research represents a significant contribution to the development and implementation of innovative approaches to the management of urban transport systems based on the principles of queuing theory, which is of key importance for improving the efficiency and sustainability of urban transport infrastructure in a rapidly changing urban landscape.
Economic analysis of the competitiveness of LLC «NESTLE KUBAN»
Authors: Агафонова Н.П. , Писарева М.А. , Зиновьев А.Д.
Published: March 2024

В статье рассматриваются теоретические и практические аспекты, связанные с оценкой конкуренции и конкурентоспособности, идентификацией ключевых факторов, влияющих на стабильность бизнеса на рынке, а также анализом конкурентных преимуществ, играющих важную роль в управлении компанией. Эти факторы определяют способность организации сохранять или увеличивать свои конкурентные позиции в условиях изменяющейся экономики и рыночной среды. Отмечается важность эффективного управления для достижения целей в текущей деятельности, а также в инвестиционной и финансовой сферах, как в краткосрочной, так и в долгосрочной перспективе.

This article examines the theoretical and practical aspects related to the assessment of competition and competitiveness, identification of key factors affecting the stability of business in the market, as well as the analysis of competitive advantages that play an important role in company management. These factors determine the organization’s ability to maintain or increase its competitive positions in the context of a changing economy and market environment. The article also considers the importance of effective management in achieving objectives in current operations, as well as in the investment and financial spheres, both in the short and long term.
Economic analysis of the growth of consumer prices for chicken eggs
Authors: Жильников А.А. , Прудников В.В. , Романов А.А.
Published: March 2024

В статье проведено экономическое исследование потребительского рынка куриных яиц на примере одного из субъектов России – Рязанской области, являющейся одним из ведущих сельскохозяйственных регионов Центрального федерального округа. Рассмотрены причины, оказавшие наибольшее влияние на увеличение стоимости куриных яиц в России, и эффективность принятых правительством мер по увеличению производства яиц и стабилизации сложившейся ситуации в стране.

The article presents an economic study of the consumer market of chicken eggs on the example of one of the subjects of Russia – the Ryazan region, which is one of the leading agricultural regions of the Central Federal District. The reasons that had the greatest impact on the increase in the cost of chicken eggs in Russia and the effectiveness of the measures taken by the government to increase egg production and stabilize the current situation in the country are considered.