Computer vision technology has advanced rapidly and made significant contributions across various fields, including object identification in images. This study aims to develop a computer vision-based system to identify fruit types from images. A machine learning model is applied using a dataset of fruit images to train the system for accurate fruit recognition. The primary processes include data acquisition, image preprocessing, feature extraction, model training, and performance evaluation. The results demonstrate a high level of accuracy in identifying specific fruit types, showcasing the potential of this technology in agricultural and commercial applications.

The rapid advancement of technology in the field of education has provided numerous opportunities to enhance the learning experience. This study focuses on the development of an Android-based learning media for introducing rare plants, specifically designed for elementary school students. The application utilizes Unity 3D to create an engaging and interactive learning environment. By integrating English language learning with botany education, the application aims to enrich students' knowledge about rare plants while simultaneously improving their English language skills. This phase is followed by the design and development stages, where Unity 3D is used to create 3D models and interactive features. The application is designed to provide an interactive and enjoyable learning experience for elementary school students to explore rare plants. By using the Android platform and Unity 3D technology, the application allows students to discover various plant names in English. Results from a trial with 20 respondents on the Android-based learning media for introducing rare plants showed that 49.35% strongly agreed, 49.25% agreed, 1.37% were unsure, 0% disagreed, and 0% strongly disagreed.

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.

This study aims to analyze the level of satisfaction with the use of the tax e-Faktur application in the tax reporting process at PT Anugerah Texindotama. The e-Faktur application is a technological innovation that facilitates electronic tax reporting, which is expected to increase compliance and efficiency in the tax administration process. This research method includes observation, interviews, and distributing questionnaires to 43 respondents who are directly related to the use of the application. Based on the results of the study, it was found that the use of the e- Faktur application has had a positive influence on user satisfaction, with an average satisfaction level of 80.83%, which is categorized as good. Several advantages of the application, such as minimizing the risk of errors and ease of access, also increase user acceptance. However, there are technical constraints that need to be improved to support system optimization. Recommendations for improvement focus on enhancing features and technical training for employees to strengthen the implementation of the e-Faktur application in corporate tax reporting.

Human resources are a company's most dominant asset, because they can play an important role in the company's business development. An outsourcing company is a legal entity and is obliged to comply with business licenses issued by the Central Government. The eligibility process for new employees is supported based on the level of ability and competency determined by the company. The existence of difficulties for companies in determining the eligibility of new employees which makes the reason for the ineffectiveness of the processes carried out by the company at this time, is used as a goal for the authors for the purposes of a study. By using the classification method in a data mining with the C4.5 algorithm (Decision Tree) and a RapidMiner application as a tool in the analysis process carried out to find a factor supporting the process of a new employee eligibility. With the data of 960 applicants used as a sample, this data was taken from 2021-2022. From the data divided into several attributes used, the highest Gain value obtained from these attributes through the results of Test 2 of 0.417152421 which will be used as the root in the process of determining employee eligibility and has the highest accuracy value of 98.44%.

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.

This study explores the implementation of Task-Based Language Learning (TBLL) in developing an Android-based application to enhance English language proficiency. TBLL was chosen for its focus on real-world language usage, enabling users to practice English skills through practical tasks. The application is developed using the Flutter framework, which supports cross-platform functionality, providing ease of access for users. The study measures the improvement in English language proficiency without relying on surveys for data collection; instead, it uses performance data from users' in-app activities. The findings are expected to demonstrate that integrating TBLL into a digital platform can effectively enhance English proficiency, especially in practical communication skills. This Android-based application implementation is envisioned as an innovative solution for flexible and efficient language learning.

The manual registration information system for incoming students is still commonly used by certain universities and colleges in Indonesia. However, the challenge lies in the fact that many potential students, especially those living outside urban areas, face difficulties with manual procedures and indeed many colleges still need a more efficient and effective information system to facilitate ownership of exam participant cards. The purpose of this study is to design a new student admissions website using PHP and MySQL to facilitate online registrants in ownership of exam participant cards. The methodology used in this study involves a system development research procedure, specifically focusing on creating a web-based system for new student admissions information that can be accessed via a web browser. The system for new student admissions information was developed using the PHP programming language and utilizing the MySQL database as a database server. The results of the design of this new student admissions website show that the newly implemented web-based student admissions system is able to offer convenience to prospective students in accessing broad information about the admissions process, as well as completing registration procedures, making online payments, and issuing exam participant cards. Hopefully this system will continue to be developed and can be applied in every college.

Motivation has an important role in the teaching and learning process for both teachers and students. For teachers, knowing students' learning motivation is very necessary. maintain and increase students' enthusiasm for learning. For students, learning motivation can foster enthusiasm for learning so that students are encouraged to carry out learning actions. Students carry out learning activities happily because they are driven by motivation. Currently, many students are less motivated to study. Backpropagation is a supervised learning algorithm and is usually used by perceptrons with many layers to change the weights connected to neurons in the hidden layer. Based on the learning rate and maximum epoch values, artificial neural networks using the backpropagation method can predict the level of student learning motivation with convergent results or the target error is achieved with an epoch of 11 iterations and a training process time (time) of 0.00.08 seconds. From the student learning motivation criteria data which is used as training data, the training targets can be identified. Yes and no input which is transformed into 0 and 1 can predict the level of student learning motivation with low, medium and high student motivation targets with reslt testing 80%.

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.