The dissemination of information at the village level is crucial for ensuring transparency to the residents. To facilitate the quick and easy communication of such information, a web-based village information system was developed. This system can be accessed by all community members, both within and outside the village, as long as they have an internet connection. Currently, Hegarmukti Village does not have an effective web-based information system, leading to delays in information delivery and a lack of accuracy. Moreover, the potential of the village remains under-promoted. This study aims to design and implement a web-based village information system for Hegarmukti Village using the Waterfall method. The system is developed using HTML for programming and MySQL for the database, with the goal of enhancing transparency and the efficiency of information dissemination. The system provides features such as village profiles, news updates, and population data searches, improving the accessibility and reliability of village information.

Introducing animals and their characteristics to mentally disabled students is a complicated matter. Mental retardation is a condition where a person's intellectual and cognitive intelligence is below average, which causes limitations in thinking, solving problems, remembering, and easily losing focus. Because of this, mentally disabled students develop more slowly than normal children their age. To help overcome developmental delays and improve their memory, special treatment and education are needed that suit their needs. Schools can utilize Augmented Reality (AR) technology as an alternative educational tool to make the teaching and learning process at school more fun, interesting and interactive so that it can leave a deep impression on students. This research aims to design and build an application to introduce animals by applying augmented reality technology. This research uses the Multimedia Development Life Cycle (MDLC) method; in this method, there are six stages: concept, design, material collection, design, testing, and distribution, with the testing method using black box testing. This research results in an Android-based augmented reality application for animal recognition for mentally disabled students. This application can make the teaching and learning process more interesting and enjoyable for students and make it easier for teachers to introduce animals and their characteristics.

In today's digital era, technology profoundly influences various societal domains, notably education. Rumah Quran Al-Inayah Pamulang, a non-formal educational center in Tangerang Selatan, fosters Quran memorization and practice among Muslim children. However, its manual system requires enhancement for better accuracy and timeliness in managing information. A web-based academic information system is proposed, utilizing the waterfall model methodology to address this. This system aims to streamline data collection, monitor memorization progress efficiently, and ensure organized data storage. The Academic Information System of Rumah Quran Al-Inayah Pamulang is a digital platform facilitating student information management, activity scheduling, academic progress tracking, and parent communication.

The process of selecting suppliers can be simplified with the aid of a system that offers recommendations for optimal supplier choices. This research aims to develop a decision support system application to assist CV. TJIGOWEK in objectively selecting tofu dregs suppliers while enhancing effectiveness and efficiency in time management. The research methodology employed to facilitate supplier selection is the Analytical Hierarchy Process (AHP). The five fundamental criteria utilized as parameters include quality, quantity, pricing, service, and payment flexibility. The AHP method is employed to determine the weight of each criterion, ultimately generating the optimal alternative ranking. The findings of this study can serve as a valuable reference for making supplier selection decisions aligned with the company's predefined criteria.

Spare parts encompass various items that are offered, owned, utilized, or consumed to fulfill consumer desires and requirements. This research implements the K-Nearest Neighbor algorithm on a test dataset consisting of 100 data objects, resulting in a novel classification perspective. The study includes a comprehensive model evaluation process involving Cross Validation on both training and testing datasets, comprising 1000 records with 36 critical and 64 non-critical outcomes. Performance assessment and testing utilizing the RapidMiner Studio application yield optimal results under various modeled scenarios. The accuracy of this algorithm model stands at 98.00%, with a standard deviation of +/- 4.00%.

This study presents a novel methodology for classifying automotive parts by implementing the Transfer Learning technique, utilizing the InceptionV3 architecture. We use a proprietary dataset encompassing diverse categories of automotive components for training and evaluating the model. The experimental findings demonstrate that this approach attains a performance accuracy level of 93.78% and a loss rate of 0.2938. The efficacy of InceptionV3 Transfer Learning in addressing the intricacies associated with automotive parts classification is demonstrated through its utilization of pre-existing knowledge from diverse domains. The resultant model reflects a capacity to accurately discern spare parts, thereby enhancing the efficiency of the automotive inventory management process. Utilizing InceptionV3 Transfer Learning in this scenario yields a notable and favorable outcome, thereby revolutionizing the traditional framework of automotive parts categorization. The model's efficacy in enhancing the efficiency and accuracy of automotive inventory management is evidenced by its achievement of a notable precision level and a minimal loss rate. The implications of these findings are significant in addressing intricate classification challenges within the automotive industry. They pave the way for utilizing intelligent technologies to optimize parts identification and management processes. This study establishes a foundation for a novel approach to comprehending and applying categorization systems for automotive components. This is achieved by harnessing the capabilities of Transfer Learning using the InceptionV3 model.

The advent of Information and Communication Technology (ICT) has significantly transformed library paradigms, shifting from traditional manual systems to digital platforms, a change particularly evident in academic libraries. This study focuses on the University of Muhammadiyah Tapanuli Selatan, aiming to develop a strategic framework for its digital library to enhance services in alignment with the tridharma of higher education. Employing a qualitative, descriptive methodology, the research incorporates both primary and secondary data sources. The analysis involves data reduction, presentation, and conclusion drawing. Results show that the University's library, accessible through Windows and Android applications, has experienced a marked increase in user engagement from 2020 to 2023. However, despite this growth, the development of the digital library requires further enhancement to fully realize its potential and meet user expectations. This study underlines the need for ongoing development strategies in digital libraries to keep pace with technological advancements and evolving user needs.

This study addresses the limited research on the user experience of e-learning platforms, specifically focusing on cognitive and emotional outcomes. The study proposes a non-invasive method to assess the emotional effects associated with e-learning platforms. The experiment involved 23 university students and compared the effectiveness of a real-time face and eye detection methodology (MIORA) with a retrospective questionnaire (SAM) to understand the emotional responses during user-platform interaction. Usability issues were intentionally introduced in the system to observe students' emotional reactions and examine the consistency between the two tools. The results confirmed the hypothesis that real-time non-invasive tools for assessing emotional reactions are more comprehensive and reliable compared to the SAM questionnaire. These tools also allow for dynamic adaptations to the site's usability and interface based on the student's emotional reactions, potentially enhancing satisfaction, and learning outcomes. These findings provide valuable insights for future research on the impact of emotional responses to e-learning platforms on user experience and learning outcomes. Ultimately, this study lays a foundation for effectively assessing the emotional outcomes of e-learning to improve online and hybrid education.

: In recent years, the integration of technology in education has sparked interest in enhancing learning experiences. Adaptive learning environments, which customize educational content and strategies to individual learners, offer a promising approach. Personalization within adaptive learning environments is crucial for addressing learner diversity and maximizing engagement and learning outcomes. This research project aims to explore the role of personalization in adaptive learning environments and its impact on the user experience and educational outcomes. By investigating the effectiveness of personalized interfaces and adaptive strategies, we seek to understand how these technologies can create more engaging and effective learning environments. The project objectives are threefold. Firstly, we aim to design and implement adaptive learning interfaces with personalized elements to customize the learning experience for each user. Secondly, we will evaluate the impact of personalization on user experience dimensions, including engagement, satisfaction, and motivation. Lastly, we will assess the effect of personalization on learning outcomes, such as knowledge acquisition and retention. This research contributes to the field of educational technology and user experience (UX) design. By examining the role of personalization in adaptive learning environments, we aim to inform the development of more effective and learner-centered educational tools and strategies.