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This study aims to analyze the impact of visual content on Instagram on users’ psychological well-being, focusing on body image, Fear of Missing Out (FoMO), and life satisfaction. As Instagram usage increases, more users are exposed to visual content promoting certain beauty standards and ideal lifestyles that are often unattainable for many. This exposure drives social comparison and FoMO, triggering various adverse effects on psychological well-being, such as low self-confidence, anxiety, and dissatisfaction with oneself. This research employed survey methods and a literature review from relevant prior studies. Findings indicate that exposure to idealized visual content on Instagram significantly intensifies body image dissatisfaction and personal insecurity. On the other hand, findings also suggest that educational and inspirational content on Instagram has the potential to support psychological well-being, though its accessibility and popularity are often overshadowed by entertainment and lifestyle content. The study concludes by emphasizing the need for users to be more selective in their content consumption and the platform’s role in promoting positive content that supports psychological well-being. This approach

The aim of this research is to analyze the influence of product quality offered through the Tokopedia application on consumer purchasing decisions. The method used is descriptive statistical analysis and linear regression testing with a quantitative approach. The research sample consisted of 110 respondents from active Tokopedia users, whose data was collected through an online survey. The research results show that product quality has a positive and significant effect on purchasing decisions. The average product quality score of respondents was 4.16, which shows consumer satisfaction with the products available. Factors such as durability, noise, and conformity to specifications are important indicators for exuding product quality. This research also shows that the features in the Tokopedia application help improve consumer perceptions of product quality. Therefore, in order for Tokopedia to remain competitive in the e-commerce market, its main focus is developing application functionality and improving product quality

This study aims to analyze the effect of product quality on purchasing decisions on the Shopee application. With the increasing use of e-commerce platforms, understanding the factors that influence consumer satisfaction and decisions is very important. The method used in this study is a quantitative approach with a descriptive design. The study population consisted of Shopee users who had made purchases, with a sample of 300 respondents taken through a purposive sampling technique. Data were collected using a questionnaire consisting of questions about product quality, reviews, prices, and purchasing decisions. Data analysis was carried out using multiple regression to test the relationship between independent and dependent variables. The results showed that product quality had a positive and significant effect on purchasing decisions, with a T-statistics value of 6.154. In addition, the promotion variable also contributed significantly to purchasing decisions. These findings indicate that improving product quality can increase consumer purchasing interest and purchasing decisions on Shopee. This study suggests that Shopee focus on improving product quality and promotional strategies to attract more customers and increase user satisfaction.

This study aims to analyze data security in popular chat applications using network forensics methods. This method enables the collection and analysis of data from networks to detect and understand potential threats or security breaches. In this research, several chat applications are analyzed to identify vulnerabilities that unauthorized parties could exploit. The results of this study are expected to provide a better understanding of the steps that can be taken to enhance data security in chat applications.    

Digitalization is the main pillar of change in various aspects of life, including education and social interaction. Balai Diklat Keagamaan Palembang has adopted digital transformation through the development of eL TV, a digital learning platform. This research aims to analyze the User Interface (UI) and User Experience (UX) on the eL TV website of the Palembang Religious Education and Training Center from an anthropological perspective using the Design Thinking method. This approach integrates aspects of culture, habits, and user behavior to create socially and contextually relevant designs. The research stages include Empathize through observations and interviews to understand user needs, Define to identify key problems, Ideate to generate creative solutions, Prototype to build an initial design that is responsive to local values, and Test to measure the effectiveness of the new design. This research concludes that an anthropological approach to UI/UX design through the Design Thinking method can increase user relevance and satisfaction with the eL TV website, while encouraging the use of technology that is more inclusive and oriented to the needs of local communities.  

The application of Internet of Things (IoT) technology in campus facility management can enhance operational efficiency and effectiveness by monitoring the availability of rooms and equipment in real-time. This study aims to explore the basic concepts and implementation of IoT in managing campus facilities through document analysis. The results show that IoT can assist in managing classrooms and equipment, allowing campus managers to optimize facility usage, reduce wastage, and improve service quality. IoT implementation also facilitates the maintenance and replacement of faulty equipment by utilizing data generated from sensors. However, the main challenges in IoT implementation are related to technological infrastructure and data security, which require special attention to ensure the system operates effectively and securely. Overall, this study concludes that IoT technology provides a solution to improve campus facility management efficiency and supports the creation of a more modern and responsive educational environment.

The development of intelligent multimedia technology has had a significant impact on various sectors, especially in education, social, and cultural fields. This article discusses the latest trends in the use of intelligent multimedia and related technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and Virtual Reality (VR), which have transformed the way we learn and interact with the world around us. In the context of education, intelligent multimedia enables a more personalized and adaptive approach to students' needs, enhancing educational accessibility, and reducing the educational gap between urban and rural areas. This technology also contributes greatly to creating a more interactive and engaging learning environment. On the other hand, the use of intelligent multimedia in social and cultural fields opens up opportunities to enrich local identities in the face of globalization, by incorporating traditional cultural elements into technology-based product designs. However, despite its many benefits, the implementation of intelligent multimedia technologies faces various challenges, such as infrastructure issues, limited budgets, and resistance from some educators who are not yet familiar with new technologies. Therefore, it is essential to ensure adequate digital literacy so that future generations can fully utilize this technology responsibly. In conclusion, intelligent multimedia has great potential to improve the quality of life, but its application must be carried out wisely, taking into account long-term impacts on society and culture.

Vertical Aquaponics System for Optimal Space Management Overview Due to rapid urban development, less land available for agriculture. Vertical aquaponics systems offer innovative solutions to overcome these problems. This research aims to design and develop a vertical aquaponic system that is efficient and effective in utilizing limited urban space. This system combines fish farming and plant cultivation simultaneously in a closed system. The nutrient-rich water from the fish pond is flowed into the plant substrate in a circular process. The vertical design of the system allows for high productivity in very limited areas. . The results of the study aim to contribute to the development of sustainable urban agriculture and increase food availability in urban areas.  Overview Due to rapid urban development, less and less land is available for agricultural activities. Vertical aquaponics systems offer innovative solutions to overcome these problems. This research aims to design and develop a vertical aquaponics system that efficiently and effectively utilizes limited space in the city. This system combines fish farming and plant cultivation simultaneously in a closed system. Nutrient-rich water from fish ponds is flowed into the plant growth substrate. The results of this research are expected to contribute to the development of sustainable urban agriculture and increase food availability in urban areas.

This research aims to analyze the best-selling products at Toko Hartati using the K-Means Clustering method. K-Means Clustering is an unsupervised learning algorithm that is effective in grouping data based on certain similar characteristics. In this context, the data used includes the number of sales, product prices, and product categories. Through this analysis, it is hoped that insight can be gained regarding products that have the best sales performance, as well as sales patterns that can be used as a reference in stock management and marketing strategies. The data used in this research includes sales transactions during a certain period, with the aim of identifying product clusters based on sales patterns. The analysis results show the existence of two main product groups, where the first cluster contains products with high sales numbers, which can be classified as best-selling products, while the second cluster includes products with lower sales. These findings provide valuable information for the management of Toko Hartati in determining more targeted marketing strategies and more efficient stock management. This research suggests using the K-Means Clustering method in data-based decision making to improve sales performance in retail stores.

Efficient energy use in household appliances has become a primary concern as awareness of environmental sustainability grows. Smart electric stoves with automatic temperature control features offer an innovative solution to enhance energy efficiency while ensuring comfort and safety during use. This study aims to design and develop a smart electric stove system based on a microcontroller with automatic temperature control algorithms. The system employs temperature sensors to detect real-time temperature changes and a Proportional-Integral-Derivative (PID) algorithm to maintain stable temperatures as set by the user. A simple and intuitive user interface is designed to facilitate operation, while the automation feature allows the system to shut off the heating element independently when the temperature exceeds a safe threshold. Test results demonstrate that the designed system can reduce energy consumption by up to 25% compared to conventional electric stoves without automatic controls. Therefore, this research significantly contributes to the development of energy-efficient and safe smart kitchen appliances.

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.

Cabinet security is generally still done manually and is still done by humans. A common problem that occurs in cabinet security is the ease of dismantling or opening cabinets by irresponsible people until theft of valuable goods or data and very important items occurs. To overcome this, a cabinet security system is needed that can increase the security of goods and data in order to minimize crime. This system is designed using a password door so that it can double the security of the cabinet. This system works when someone wants to open the cabinet door using a password sent via callphone then processed by a microcontroller and displayed by the LCD after using being processed if the password is correct then door will open. The implementation of this system is expected to increase security in cabinets so that they can store important goods or data more safely and the level of security that previously used a manual key is doubled.

This Electronic Medical Record is a digital version of a medical record, the same as a paper-based manual medical record, this electronic medical record also contains information regarding health history, diagnoses, laboratory results, examination notes, medications given, medical procedures, and other data. relevant to the patient's health condition. It is hoped that the implementation of Electronic Medical Records can increase the efficiency of BPJS claims and improve the quality of service. Therefore, this study aims to analyze the use of RME using the Delone and Mclean method. The Delone and Mclean method is an information system quality evaluation framework that includes six dimensions, namely information system quality, information quality, service quality, use quality, user satisfaction, and user impact. In this study, we apply this method to analyze the quality of RME management. This research uses a quantitative approach by collecting data through questionnaires distributed to RME users in hospitals. The questionnaire measures user perceptions of information system quality, information quality, service quality, use quality, user satisfaction, and impact of using RME. The results of this research are expected to provide better insight into the use of RME in the context of work efficiency. The findings of this research will provide input for RME developers to improve the quality of information systems, the quality of information, and the quality of services provided to users. Apart from that, this research also contributes to theory and research in the field of information systems by applying the Delone and Mclean method in the context of RME management.

Online learning has become an essential component of modern education; however, conventional online learning platforms often rely on two-dimensional interfaces that limit user engagement, interaction, and immersion. These limitations reduce learning motivation and hinder the creation of an effective learning experience, particularly for activities that require active participation. To address these challenges, this research focuses on the design of User Interface (UI) and User Experience (UX) for online learning implemented in a Virtual Reality (VR) environment. The objective of this study is to develop a user-centered VR-based online learning interface that enhances interaction, usability, and learning comfort. This research applies the Design Thinking methodology, which consists of five stages: empathize, define, ideate, prototype, and test. User needs and usability issues were identified through observations and interviews, followed by interface design and prototype development of a VR learning environment featuring chat rooms, whiteboards, slide presentations, and virtual representations of teachers and students. Usability evaluation was conducted using the Maze platform to measure user success rates in completing predefined tasks. The results show that 80% of users completed tasks through the expected interaction paths, exceeding the minimum usability threshold of 70%, while 20% of users failed to complete the tasks, indicating areas for improvement. These findings demonstrate that the proposed UI/UX design effectively supports user interaction and usability in a VR-based learning environment. In conclusion, this study confirms that integrating Design Thinking into the UI/UX design process contributes to the development of effective and user-centered VR-based online learning systems, while also highlighting the importance of usability evaluation for refining immersive educational interfaces.

This study aims to evaluate customer satisfaction with the menu offerings at "Rajanya Seafood" using the Lean Startup approach. This method was chosen because it enables businesses to develop products that better meet customer needs and preferences through rapid experimentation cycles, continuous feedback, and regular updates. Research data was collected through direct surveys of "Rajanya Seafood" customers, focusing on aspects such as taste quality, menu variety, pricing, and service. The collected data was analyzed to identify areas needing improvement as well as potential innovations to enhance customer satisfaction. The study results indicate that the Lean Startup approach is effective in quickly understanding and responding to customer needs, thus contributing to increased customer loyalty and satisfaction. These findings are expected to serve as a reference for "Rajanya Seafood" and other culinary businesses in applying the Lean Startup strategy to achieve optimal customer satisfaction levels.      

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 Utilization of GPS and GSM technology in operational vehicle monitoring offers convenience and efficiency in management. This research designs a GPS-based vehicle monitoring system that is integrated with vehicle maintenance management to assist companies in making decisions related to fuel efficiency, predictive maintenance scheduling, and safety aspects. By monitoring vehicle position and condition in real-time, companies can optimize travel routes, reduce travel time and reduce operational costs. The system also includes tire pressure and fuel percentage monitoring, which serve as important indicators in an accurate and sustainable vehicle maintenance strategy. This research uses quantitative methods to analyze various aspects in designing a GPS-based monitoring system that is integrated with operational vehicle maintenance management. With the resulting data, managers are able to identify trends that support predictive maintenance as well as preventive steps to reduce the risk of sudden damage. The research results show that the integration of GPS and GSM provides significant benefits in improving performance and reliability for vehicles, especially in the distribution and logistics sectors. The implementation of this system is expected to support the company in maintaining optimal vehicle performance and contribute to operational sustainability.

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.