Palembang Religious Education and Training Center as an education and training institution utilizes information technology, especially wifi internet networks to support various learning and training activities. To support these needs, a quality internet network is needed, so an evaluation and measurement of Quality of Service (QoS) is needed, because QoS is able to measure various important parameters in the network, such as throughput, delay, jitter, and packet loss, all of which play an important role in ensuring the network functions properly.  The standard used is TIPHON. By using the Action Research method, this research will produce real internet quality data in accordance with actual conditions. After testing, the average results on the 4 parameters tested obtained an index value of 3. So that the overall quality of the internet network at the Palembang Religious Education and Training Center has good network quality.

Rice pest control is one of the main challenges in the agricultural sector in Indonesia. Pests such as planthoppers, stem borers, and rats can cause significant losses to crop yields. Currently, many farmers have difficulty identifying pest types and how to control them quickly and effectively. Therefore, a technological solution is needed that can detect pests directly and provide recommendations for action. This study aims to design an Android-based application that is able to detect types of rice plant pests using visual images and provide recommendations for handling. This application is designed using digital image processing methods and is supported by a large pest database. This technology is expected to be an efficient and practical solution for farmers. The research method used in developing this application is a qualitative method, involving interviews with farmers, agronomists, and data collection related to pests and their damage patterns. This application utilizes AI-based pattern recognition technology to detect pests through photos taken directly by farmers. The results of the study showed that this application was able to detect several types of major pests with an accuracy of up to 85%. In addition, this application provides recommendations for handling steps based on guidelines from the Ministry of Agriculture. The trial showed that this application can help farmers identify pests faster than manual methods. The main contribution of this research is to create a technology-based solution to agricultural problems in Indonesia, especially in the rice sector. With this application, farmers can increase their yields through early identification and proper pest management. In future implementations, this application will continue to be developed to detect additional pests and expand its database. It is hoped that this application can be an important tool in supporting smart farming in Indonesia.

This research focuses on designing and simulating a makeup robot control system with a Human-Robot Interaction (HRI) approach. The main goal is to develop a robot that is not only efficient in applying makeup, but also able to interact directly with users. The design of this robot is designed with attention to anthropomorphism and non-verbal interaction, in order to improve user comfort and experience during the use process. This control system leverages cutting-edge sensor technology, such as facial recognition and expression analysis, to detect user emotions and adjust the robot's response in real-time. The simulation process is carried out using the Robot Operating System (ROS) to develop an algorithm that supports task coordination between robots and humans as well as interactive feedback. The results of the simulation show that the robot is able to recognize the user's emotions and adjust their actions, thus creating a more intuitive and responsive interaction experience. This research has made a significant contribution to the development of robotics technology in the field of beauty, thereby improving the user experience in personal care. The findings also pave the way for further research into more complex human-robot interactions that are responsive to individual needs.

The development of Virtual Reality (VR) technology opens up new opportunities to improve the quality of online learning through more interactive and immersive learning experiences. This study aims to design the user interface (UI) and user experience (UX) of VR-based online classes using the Design Thinking method to meet students' needs in a virtual learning environment. The Design Thinking method, which includes the stages of empathy, definition, ideation, prototype, and testing, is applied to produce a user-friendly interface design that supports student engagement and social interaction during the learning process. The results of the study show that the VR-based interface is able to increase student engagement through more active interactions, intuitive navigation, and collaboration features that approach interactions in a physical classroom. Testing of the prototype shows that this design can meet students' needs in increasing engagement and learning comfort. It is hoped that this study can be a reference in the development of an effective and efficient VR-based online learning platform.

This study seeks to create a system for monitoring the environment using the Internet of Things. It aims to help farmers manage their rice fields in a way that is both effective and sustainable. The system will provide farmers with real-time data on soil moisture, air temperature, and rainfall, allowing them to make informed decisions. Sensors will collect this information, which will be analyzed and presented simply through a web or mobile app. Early simulations suggest that this system could boost crop yields by as much as 15% and cut water use and costs by 20%. These findings point to the IoT monitoring system as a practical means to enhance rice farming's efficiency and productivity. Yet, there are hurdles. Issues like poor network infrastructure, high costs of implementation, and the farmers' ability to adapt to this technology need to be overcome for the system to work properly. This study aspires to make a real difference in promoting sustainable farming practices while paving the way for more advanced IoT solutions in the future.

In the animation industry, the effectiveness of user interface (UI) and user experience (UX) design in image processing software is crucial for enhancing user comfort and productivity. This study aims to evaluate the UI/UX design in software belonging to the Adobe family, such as Photoshop, Illustrator, and After Effects. The employed methodology is Design Thinking, which includes the steps of Empathize, Define, Ideate, Prototype, and Test, to analyze each aspect of UI/UX design. Data were gathered through surveys and interviews with industry professionals to understand their experiences and perspectives. Preliminary results indicate that while Adobe applications are generally satisfactory, some software like After Effects and Illustrator require specific adjustments to the workspace menu to better meet user needs. These findings highlight areas needing improvement in image processing software to enhance user comfort and work efficiency. This research is expected to contribute to the development of more user-centered software, thereby improving user experience quality in the animation.

The Water Quality Index (WQI) shows the condition of water quality in an area based on the status of water quality resulting from the measurement of physical, chemical and bacteriological parameters of a water body both rivers and lakes. Several machine learning techniques can be used to predict water quality in an area, one of which is through the prophet model approach which is able to provide fairly accurate predictions for the water quality index in Indonesia. The main objective of this research is to obtain a WQI prediction value as a baseline in the formulation of future environmental control activity policies using the prophet model. The result is that the predicted value of IKA for 2021-2023 generated through machine learning with the prophet model approach shows that the Mean Absolute Error (MAE) value: 7.01, Root Mean Square Error (RMSE): 8.61 and Mean Absolute Percentage Error (MAPE): 13.06%, which means that IKA prediction with the prophet model is effective in capturing annual patterns between historical data and future predictions.
 
 

The function of artificial intelligence (AI) in creating a positive consumer experience on the Shopee e-commerce platform is covered in this study. Nowadays, artificial intelligence (AI) plays a significant role in the e-commerce sector, allowing businesses to offer more individualized, quick, and safe services. This study examines how Shopee customer satisfaction and loyalty are impacted by the use of AI technologies, including chatbots, tailored product suggestions, fraud detection, and inventory management. This study found that AI plays a significant role in making shopping more responsive and convenient by analyzing data on the use of chatbot services, the efficacy of personalized recommendations, the accuracy of predicting customer needs, transaction security, and the efficiency of logistics management. According to the study's findings, implementing AI technology reduced service response times by up to 20% and increased customer satisfaction by 15%. In addition to enhancing service quality, the use of AI increases Shopee customer loyalty. These results demonstrate how AI in e-commerce holds enormous promise for fostering startup expansion and enhancing client connections.

Abstract. One example of advanced information and communication technology is the internet. One can readily obtain the knowledge they require thanks to the internet. As a result, the internet is a crucial tool that needs to be used and understood to the fullest. The internet may be used for both beneficial and harmful purposes, which is why it is a double-edged sword with all of its risks. By filtering negative content using a list of 773 thousand negative content blocked on the trust + ™ Positive website by the Ministry of Communication and Information, the author hopes to create a positive internet network in the Prabumulih community and enable effective and efficient use of internet resources. The author can create a favorable online environment in Prabumulih City by utilizing the action research approach and the policy zone response method.

Security of electronic medical records (EMR) data is very important in maintaining the confidentiality, integrity, and availability of sensitive patient information. This study aims to conduct a security analysis of the EMR application used at UPTD RSD Besemah Pagar Alam City using the Penetration Testing method. This method is carried out to identify, exploit, and provide solutions to potential vulnerabilities in the EMR application system. Penetration Testing is carried out through several stages, namely information collection, scanning, exploitation, and post-exploitation, using tools such as Nmap, and OWASP ZAP. The results of the study showed several vulnerabilities in the application, including SQL Injection, Cross-Site Scripting (XSS), and weaknesses in authentication management that could allow unauthorized access to patient data. In addition, exposure to sensitive data that was not properly protected was also found. Based on the results of this test, several recommendations were made to improve system security, such as updating security patches, implementing encryption on all sensitive data. By implementing the recommended mitigation steps, the security of the EMR system at UPTD RSD Besemah is expected to be significantly improved, so that the risk of data leakage can be minimized. This research provides a real contribution in strengthening the security of electronic medical record applications. and is expected to be a reference in improving security systems in other health care institutions.