The application of the MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) method in employee promotion decisions at PTPN 4 aims to enhance efficiency and objectivity in decision-making. This method allows managers to evaluate employees based on multiple criteria simultaneously, such as performance, experience, contributions, and other relevant factors. By considering these various aspects, MOORA helps make promotion decisions more transparent and fair. One of the primary advantages of applying the MOORA method is its ability to reduce bias that may occur during the promotion process. Bias can arise from subjectivity or imbalance in employee assessments, which are often based on individual judgments or personal perceptions. By using MOORA, promotion decisions are based on more objective and measurable data, making the process more systematic and structured. The MOORA method can also increase employee motivation. A transparent promotion process based on clear criteria provides employees with a strong incentive to continuously improve their performance. When employees know that promotions are based on fair evaluation, they are more motivated to work harder. This, in turn, will increase overall productivity and performance at PTPN 4. The implementation of MOORA at PTPN 4 also provides advantages in better human resource management. With the MOORA-based decision support system, managers can easily identify employees who have the best potential for promotion. This process involves several steps, such as data normalization, determining criteria weights, and calculating final values that reflect overall employee performance. The end result is the selection of employees who meet the qualifications and have outstanding performance for promotion, supporting the sustainable development of the organization.

This study compares the performance of two deep learning models, namely Convolutional Long Short-Term Memory (ConvLSTM) and Long-term Recurrent Convolutional Network (LRCN), in the task of recognizing human activity from videos. Human activity recognition is an important field in computer vision with many applications, such as security monitoring, human-computer interaction, and social media-based video analysis. ConvLSTM is a model that combines convolution operations with long-term memory LSTM, thus capable of capturing spatial and temporal information simultaneously. This approach is ideal for processing video data sequences that have spatial and temporal dimensions. On the other hand, LRCN combines the power of spatial feature extraction from Convolutional Neural Network (CNN) and temporal sequence modeling through Recurrent Neural Network (RNN), specifically LSTM, to understand movement patterns in videos. The study used the UCF50 dataset consisting of 50 activity classes, but was limited to five classes for the focus of the experiment. The dataset was divided into 80% for training and 20% for testing, and the model was drilled for 50 epochs using early stopping to prevent overfitting. The results show that both models have high training performance. ConvLSTM achieved a training accuracy of around 98% and a validation accuracy of 90%, while LRCN achieved a training accuracy of 99.5% and a validation accuracy of 88%. Although ConvLSTM demonstrated good stability on the validation data, further testing using TikTok videos as real-world data showed that LRCN had a higher confidence level in recognizing activities, with most predictions achieving confidence scores above 80%. This difference in performance indicates that while ConvLSTM excels in generalizing on training data, LRCN is more robust to real-world data variations.

The transition of children from early childhood education to elementary school (SD) is a critical phase in their psychological and academic development. During this phase, children face significant challenges, including changes to a more structured learning environment and increasing academic demands. At SDN 055991 in Langkat Regency, this phenomenon is reflected in the difficulties experienced by some students, particularly with basic skills such as reading, writing, and arithmetic, as well as with socializing with peers. These difficulties can impact children's long-term academic and social development. This study aims to identify the key factors influencing children's learning readiness during this transition period, utilizing artificial intelligence (AI) technology. Specifically, this study uses Artificial Neural Networks (ANN) and Decision Trees as tools to analyze the data obtained. The use of this data-driven approach allows for a more in-depth analysis of the complex patterns and relationships between various variables that influence children's learning readiness, such as family factors, social environment, and students' basic skills. This study also references various previous studies demonstrating the effectiveness of backpropagation and Deep Learning algorithms in the context of education and student performance prediction. This approach is expected to provide more precise solutions for understanding children's learning readiness and provide a more accurate picture of the factors contributing to difficulties experienced by students in the transition to elementary school. The results of this study are expected to provide relevant recommendations for parents, educators, and education policymakers to support children's learning readiness and strengthen basic education policies that are adaptive to the needs of students in this digital era.

The term "cloud computing" refers to the delivery of numerous services via the Internet. Because of providers that provide cloud services, users can store files and media on faraway servers and subsequently access the items online. Due to the lack of location requirements, this enables anyone to watch them remotely. This design is currently beginning to be implemented in the sphere of education, particularly in universities. In order to determine the factors influencing the adoption of cloud computing in education, previous academics have employed the technology adoption theory, which is discussed in this study. The purpose of this study, which is a systematic literature review, is to identify and assess knowledge gaps about the factors impacting the adoption of cloud computing in education. To fill in any gaps and add to the body of knowledge already in existence, this study will therefore enhance the information by offering a complete examination of the material that is already available.

Advances in augmented reality (AR) technology have opened up new possibilities in learning, such as help with mathematics. The aim of this research is to develop a simple interactive learning application for building rooms based on AR technology using Unity and Vuforia Engine. This application is designed to help students understand spatial geometry concepts visually and interactively so as to increase interest and understanding of the subject matter. This application development uses Unity as a development platform and Vuforia Engine as an SDK to facilitate AR integration.  This application creates a more interesting learning experience and supports the visualization of geometric objects such as cones, cubes, tubes, balls and pyramids. AR technology allows students to interact with these objects in a 3D environment, which can be very helpful in clarifying concepts and formulas that are difficult to understand using traditional learning media. It is hoped that this research can provide innovative solutions to improve the quality of geometry learning in schools.

Management Information Systems (MIS) are an important component in modern organizational operations which function to manage, process and disseminate information to support decision making, planning and control. This article discusses the basic concepts of MIS, including its definition, components and functions in an organizational context. MIS consists of hardware, software, data, procedures and human resources that interact to produce relevant and accurate information. The key role of MIS in improving operational efficiency, simplifying business processes, and providing timely reports to managers is explored in depth. In addition, this article also discusses the latest challenges and trends in MIS development, including issues of data security, system integration, and adoption of new technologies. Through a deep understanding of the basic concepts of MIS, organizations can more effectively utilize information technology to achieve their strategic goals.

The growth of the internet has influenced the tourism industry because the internet makes it easier for individuals to obtain reviews about places to visit and because the internet is a tool used by tourist site managers to assess the quality of their offerings. The increase in the number of tourists of almost two million in just three years in West Sumba is proof of this influence. Social media is a tool that people use to interact with each other online; some people have multiple accounts on platforms such as Instagram, WhatsApp, Facebook, Telegram, Twitter, and so on. Tourists can receive recommendations for tourist attractions based on price and type of trip desired through a tourist attraction recommendation system that uses the KNN algorithm. Three factors were used in this research: activity, type of tourism, and type of price. An accuracy of 63.16% is found in the test results using the KNN algorithm and the Rapid Miner application with a K value of 5. The analysis results show that the K-Nearest Neighbor (K-NN) approach can be used as a guideline for recommending tourist destinations to visitors in West Sumba.

The Village Office is the village administration center in rural areas. The function of the village government is to carry out village administration which is carried out by the village head, village officials and the village residents themselves. In Rada Mata Village, Tambolaka City District, Southwest Sumba Regency, it is one of the villages that already has internet access. The village makes it easy to access sites on the internet. Therefore, the aim of this research is to create a system capable of managing population information data. The results obtained from this research are a population information system that can solve the problems faced by Rada Mata Village. From the results of the discussion it can be concluded that the population information system can answer the problems faced, including making data searches easier and faster, archiving data does not take up a lot of space because it has been replaced by digital storage, and data reporting can be presented quickly, completely, attractively and appropriately. village needs.
 
 

In the current digital era, cybersecurity of data and information systems. The threat of  attacks, or , is a form of threat that continues to grow along with advances in technology. This research aims to learn about cybersecurity strategies in dealing with . The method used in this research is a literature review. This journal was prepared based on an analysis of research results from various journals accessed through secondary data sources, namely the Google Scholar database, and e-resources from Springer, Cambridge, and Taylor and Francis. The research results show that implementing technology such as encryption, multifactor authentication, and user training, are some of the effective steps that have been proven to reduce risk. However, challenges in implementing this strategy remain, both from a technical and non-technical perspective, which require special attention from researchers and practitioners in the field of cyber security.

In today's digital era, technology and information are developing very rapidly. The role of technology has brought benefits to humans in all aspects of the field, namely education, economics, social and culture, transportation, etc. With increasingly advanced technology, it is hoped that it will make human work easier in the future. Digital technology has changed the way we work, interact and do business. In today's digital era, old systems and processes must be rethought, and new technologies must be implemented so that businesses remain competitive and grow. High global competition places demands on business actors to continue to improve product innovation by utilizing existing technology to face this global challenge. Utilization of technology such as Increasing Operational Efficiency and Global Business can also help in understanding the changes that occur in the digital business ecosystem. The aim of this research is to determine the influence of digital technology on the development of modern business.